该页无缩略图
数据科学学院
Combining Tradition
with Modernity
Bringing Together China
and the West
THE CHINESE UNIVERSITY OF HONG KONG, SHENZHEN
Graduate with a degree from a university ranked in the globally
All courses taught in English except Chinese and PE
TOP
50
CONTENTS
02
04
06
18
26
38
42
46
50
52
54
Dean’s Message
院长致辞
School of Data Science
数据科学学院
Faculty
师资力量
Undergraduate Programmes
本科专业
Data Science and Big Data Technology
数据科学与大数据技术
Statistics
统计学
Computer Science and Engineering
计算机科学与技术
Financial Engineering
金融工程
Taught Postgraduate Programmes
硕士项目
Master of Science in Data Science
数据科学理学硕士
Master of Science in Financial Engineering
金融工程理学硕士
Master of Science in Bioinformatics
生物信息学理学硕士
Master of Science in Artificial Intelligence and Robotics
人工智能与机器人理学硕士
Research Postgraduate Programme
博士项目
Ph.D. Programme in Data Science
数据科学博士
Ph.D. Programme in Computer Science
计算机科学博士
Academic Achievements
学术成就
Student Achievements
学生成就
International Programmes
国际交流
Further Study and Employment
升学 / 就业
Activities
活动
* 手册将持续更新 / Continually updating
目录
DEAN’S MESSAGE
院长致辞
我们现在身处一个数据的时代。基于数据和算法所
产生的智能决策已经成为人们生活中重要的组
成部分。如何利用安全、公平以及高效的算法
来创造价值已经成为各行各业关注的重要问题。在此背
景下，香港中文大学（深圳）数据科学学院于 2020 年 7
月 1 日正式成立。地处中国创新之都深圳，数据科学学
院致力于为学生提供多元发展的优质环境，充分发挥学
生潜能，培育具有全球视野的顶尖创新型人才 , 矢志成为
大湾区乃至全世界领先的数据科学教学和科研中心。
雄厚的师资力量为数据科学学院的发展奠定了坚实
的基础。学院大量教职成员曾在国际顶尖大学担任终身
教授，并为数据科学众多领域国际上引领方向的学者。
数据科学学院已建立了从本科到博士完整的培养体系，
包括数据科学与大数据技术、计算机科学与技术、统计学、
金融工程四个本科项目；数据科学、金融工程两个硕士
项目以及数据科学、计算机科学两个博士项目。数据科
学中最前沿的核心课程如机器学习、人工智能等将贯穿
各个项目，给本科生、研究生提供系统、前沿的数据科
学方面的教育，拓宽学生的视野，打开未来数据科学研
究与应用的大门。这些项目的毕业生大量前往世界顶尖
大学继续深造，其中不乏被斯坦福大学、麻省理工学院、
哥伦比亚大学、康奈尔大学等世界最顶尖学府以全额奖
学金录取攻读博士学位的同学。
数据科学学院吸引了来自计算机科学、运筹学以及
统计学等多学科的教授队伍。这种多学科的体系将促进
基础研究和应用研究的平衡发展。目前，学院的应用研
究领域包括：生物信息学、通讯系统、金融、人工智能
医学诊断、精准医疗、云计算、机器人技术、物流和供
应链管理等。其中许多应用研究已通过一系列深度合作
实践于众多实验室与研究院，如腾讯联合实验室、京东
联合实验室、华为联合实验室、深圳市大数据研究院和
深圳市人工智能与机器人研究院。
社会的发展带来了对数据科学人才的需求，同时也
带给我们巨大的责任与挑战。我们将始终以人才培养和
科学研究为己任，积极开展与国内外的交流与合作，努
力将学院建设成数据科学人才培养的优质基地，同时也
成为国际一流的研究、交流与合作中心。 在此，我们诚
挚欢迎有理想的优秀学者、学生和老师加入我们的团队，
为实现这个目标共同努力！
02 School of Data Science
戴建岗 Prof. Jim Dai
数据科学学院院长
康奈尔大学Leon C. Welch讲座教授
Dean of School of Data Science
Leon C. Welch Professor (Cornell University)
We now live in a time of big data. The intelligent
decisions generated by data and algorithms
have become an important component of
our daily life. How to create value from secure, fair,
and efficient algorithms has become an important
challenge faced by every industry in our society.
With such a background, the School of Data Science
(SDS) of The Chinese University of Hong Kong,
Shenzhen is established on July 1st, 2020. Located
in Shenzhen, the innovation hub of China, the SDS
is committed to providing students with a vibrant and
diverse environment to fully develop their potentials
and to cultivating top innovative talents with a global
perspective. Our goal is to become the leading teaching
and research center of Data Science in the Greater Bay
Area and worldwide.
The world-class faculty is the foundation of the School of
Data Science. Many faculty members have been tenured
professors in top universities in the world, and are
international leaders in their respective fields. Currently,
the school offers a comprehensive set of education
programmes, including four undergraduate programmes,
two master programmes, and two Ph.D. programmes.
The four undergraduate programmes are in Data Science
and Big Data Technology, Computer Science and
Engineering, Statistics, and Financial Engineering. The
two master programmes are Master of Science in Data
Science and Master of Science in Financial Engineering.
The Ph.D. programmes are in Data Science and
Computer Science. Core courses in data science such as
machine learning and artificial intelligence will be offered
across all programmes and to students at all levels. Such
a systematic and state-of-the-art education opens the
future of data science research and applications to all
students. Among past graduates of these programmes,
many have gone to top universities around the world for
graduate studies including some being admitted with
Ph.D. programmes in full scholarship at universities of
Stanford, MIT, Columbia, and Cornell.
The School of Data Science has attracted faculty
members from multiple disciplines including computer
science, operations research, and statistics. This
multidisciplinary structure promotes a natural balance
between foundational research and applied research.
Current applied research areas include bioinformatics,
communications systems, finance, AI medical diagnosis,
precision medicine, cloud computing, robotics,
logistics and supply chain management. Many of these
applied researches have been carried out through our
collaboration with Tencent Joint Lab, JD Joint Lab,
Huawei Joint Lab, as well as Shenzhen Research
Institute of Big Data (SRIBD), and Shenzhen Institute of
Artificial Intelligence and Robotics for Society (AIRS).
The development of our society brings us the demand for
talents in data science. At the same time, it brings huge
responsibilities and challenges to us. We will always take
first-class teaching and research as our responsibilities.
In the meantime, we will actively promote exchanges
and collaborations with colleagues at home and abroad,
in order to make the SDS a center for high-quality
talents in data science, as well as an international hub
for research and collaboration. Here, we sincerely invite
researchers, scholars and students who share our vision
to join us, and achieve this goal together!
Dean’s Message
sds.cuhk.edu.cn 03
SCHOOL OF DATA SCIENCE
数据科学学院
香港中文大学（深圳）数据科学学院成立于 2020 年 7 月。
数据科学学院专注于数据科学方向的人才培养与科学研
究。学院在运筹学、统计学、计算机科学等基础领域以及运营
管理、决策科学、机器学习等前沿领域有着系统的教学体系，
为学生提供完整且前沿的理论与实践培养。学院强调产学研结
合，秉承香港中文大学（深圳）“致力于培养具有国际视野、
中华传统和社会担当的创新型高层次人才”的育人目标，为学
生提供多元发展的优质环境，充分发展学生潜能，矢志成为世
界领先的数据科学创新与科研基地，培育具有全球视野的顶尖
创新型人才。
数据科学学院拥有雄厚的师资力量。学院教授队伍均拥有
世界一流院校的博士学位，许多教授曾在世界顶尖大学任教，
在学术界和工业界相关领域具有显著影响力。学院曾举办多场
国际数据科学相关会议及活动，在国际上拥有一流声誉。
成立数据科学学院标志着香港中文大学（深圳）在数据科
学方向继续加大投入，也体现了香港中文大学（深圳）坚定站
在时代发展的前列，为社会培养时代发展所需人才的决心。
The School of Data Science (SDS) of The Chinese University
of Hong Kong, Shenzhen is established in July 2020.
The SDS focuses on first-class teaching and academic
research in data science. It has established a systematic
education system in data science, including theoretical
aspects such as operations research, statistics, computer
science, and application fields such as machine learning,
operations management, and decision analytics, providing
students with comprehensive and state-of-the-art training.
With the aim “to nurture high-end talent with global
perspectives, Chinese tradition and social responsibility” ,
the school is organically combining industry, education and
research, determined to become the world's leading data
science innovation and research base, as well as cultivating
top innovative talents with a global perspective.
The SDS is established on a solid foundation with a strong
faculty team. All faculties in the SDS have doctoral degrees
from world-class universities. Many of them also have
experience in working in top-tier universities in the world
and have a significant international impact in related fields of
academia and industry. Besides, the school has held many
international data sciences related conferences and events
and established recognition in the world.
The establishment of the SDS represents the increasing
investment of The Chinese University of Hong Kong,
Shenzhen in the field of data science, which is also a sign of
the determination of The Chinese University of Hong Kong,
Shenzhen to stand at the forefront of the era and to cultivate
the talents needed for the development of the society.
School of Data Science
sds.cuhk.edu.cn 05
斯坦福大学博士
国际数理统计学会会士、运筹学和管理科学协会会士，曾获INFORMS应用概率学会Erlang
奖、The ACM SIGMETRICS 终身成就奖（迄今唯一华人获奖者），《运筹学数学》前主编
研究领域：应用概率、流体模型、扩散模型、随机过程及强化学习、随机处理网络中的动态资源
分配和优化及在半导体晶圆生产线、通信网络、数据中心和服务系统（客户呼叫中心、打车平
台、航空公司、医院等）的应用
Ph.D., Stanford University
Experience: IMS Fellow, INFORMS Fellow, The Erlang Award from the INFORMS Applied Probability
Society, The ACM SIGMETRICS Achievement Award, Former Editor-in-Chief of Mathematics of
Operations Research
Research Field: Applied Probability, Fluid Models, Diffusion Models, Stochastic Processes and
Reinforcement Learning, Dynamic Resource Allocations in Stochastic Processing Networks and Their
Applications to Semiconductor Wafer Fabrication Lines, Communications Network
戴建岗
DAI, Jiangang Jim
院长
康奈尔大学
Leon C. Welch讲座教授
Dean,
Leon C. Welch Professor,
Cornell University
06 School of Data Science
FACULTY
师资力量
康奈尔大学博士
国际运筹与管理协会会士、制造与服务运营管理协会杰出会士、中国香港工程师学会会士，
全球Top 2%顶尖科学家、哥伦比亚大学刘氏家族冠名教授、香港科技大学嘉柏有限公司冠
名工程学教授、曾获INFORMS 2011收益管理与定价领域历史奖、INFORMS 2012 实践
奖、INFORMS 2016 影响力奖、INFORMS 2005 和 2021收益管理与定价领域奖，曾任哥伦
比亚大学工业工程与运筹学系主任年和香港科技大学工业工程与决策分析系主任
研究领域：动态定价、离散选择模型、品类优化、定价分析、动态规划
Ph.D., Cornell University
Experience: INFORMS Fellow, MSOM Distinguish Fellow, HKIE Fellow, World’s Top 2% Scientists,
Liu Family Professor Emeritus at Columbia University, Crown Worldwide Professor Emeritus at the
Hong Kong University of Science and Technology, Recipient of the 2011 Historical Award of the
INFORMS Revenue Management & Pricing Section, the 2012 INFORMS Practice Award, the 2016
INFORMS Impact Prize, the INFORMS Revenue Management & Pricing Section Prize (2005 and
2021), Former Chairman of the Industrial Engineering and Operations Research (IEOR) Department
at Columbia University, Former Head of the Department of Industrial Engineering and Decision
Analytics at the Hong Kong University of Science and Technology
Research Field: Dynamic Pricing, Discrete Choice Models, Assortment Optimization, Pricing Analytics,
Dynamic Programming
GALLEGO,
Guillermo
校长学勤讲座教授
X.Q. Deng Presidential
Chair Professor
麻省理工学院博士
中国工程院外籍院士、加拿大皇家科学院院士、国际电气与电子工程师学会会士、美国工业与应用数
学学会会士、全球Top 2%顶尖科学家、全球前1000位计算机科学和电子领域顶级科学家、深圳市大
数据研究院院长、香港中文大学（深圳）-腾讯 AI Lab 机器智能联合实验室主任、华为未来网络系统
优化创新实验室主任，荣获第一届王选应用数学奖（2022）
研究领域：大数据分析的最优化方法、信号处理中的算法设计与复杂性分析、数据通信
Ph.D., Massachusetts Institute of Technology
Experience: Foreign Member of the Chinese Academy of Engineering, Fellow of the Royal Society
of Canada, IEEE Fellow, SIAM Fellow, World’s Top 2% Scientists, Top 1000 Scientists in Computer
Science and Electronics, Director of Shenzhen Research Institute of Big Data, Director of CUHK (SZ)-
Tencent AI Lab Joint Laboratory of Machine Intelligence, Director of Huawei Innovation Laboratory for
Future Network Systems Optimization, the First CSIAM Wangxuan Prize (2022)
Research Field: Optimization Methods for Big Data Analytics, Complexity and Computational Issues
arising from Signal Processing, Digital Communication
罗智泉
LUO, Zhiquan Tom
副校长（学术）
校长学勤讲座教授
Vice President (Academic),
X.Q. Deng Presidential
Chair Professor
华南理工大学博士
新加坡工程院院士、国际电气电子工程师学会和国际语音通信学会会士、亚太人工智能学会AAIA会
士、全球Top 2%顶尖科学家、国际语音通信学会主席（2015-2017）、亚太信号与信息处理协会
主席（2015-2016）、亚洲自然语言处理联合会主席（2017-2018），曾获新加坡总统科技奖、
《IEEE计算智能杂志》和《神经网络与学习系统汇刊》最佳论文奖，曾任顶级期刊IEEE/ACM《音
频、语音和语言处理汇刊》主编，曾任ACL、INTERSPEECH、ICASSP等大会主席，原新加坡国立
大学终身教授、德国不来梅大学卓越讲座教授
研究领域：语音信息处理、自然语言处理、类脑计算、人机交互
Ph.D., South China University of Technology
Experience: SAEng Fellow, IEEE/ISCA Fellow, AAIA Fellow, World’s Top 2% Scientists, President of ISCA
(2015-2017)/APSIPA (2015-2016)/AFNLP (2017-2018), Singapore President's Technology Award,
Outstanding Paper Award of IEEE Computational Intelligence Magazine/IEEE Computational Intelligence
Society Outstanding TNNLS, Former Editor-in-Chief of IEEE-ACM Transactions on Audio Speech and
Language Processing, Former Member of IEEE Speech and Language Processing Technical Committee,
Former General Chair of ACL/INTERSPEECH/ICASSP, Former Professor with Tenure at the National
University of Singapore, Bremen Excellence Chair Professor at the University of Bremen
Research Field: Speech Information Processing, Natural Language Processing, Neuromorphic
Computing, Human-Computer Interface
李海洲
LI, Haizhou
执行院长
校长学勤讲座教授
Executive Dean,
X.Q. Deng Presidential
Chair Professor
查宏远
ZHA, Hongyuan
副院长（科研）
校长学勤讲座教授
Associate Dean (Research),
X.Q. Deng Presidential
Chair Professor
斯坦福大学博士
全球Top 2%顶尖科学家、全球前1000位计算机科学和电子领域顶级科学家，曾获NeurIPS杰出
论文奖、Leslie Fox数值分析奖，SIGIR最佳学生论文奖指导教授，深圳市人工智能与机器人研究
院副院长、原佐治亚理工学院教授
研究领域：机器学习及应用
Ph.D., Stanford University
Experience: World’s Top 2% Scientists, Top 1000 Scientists in Computer Science and Electronics,
NeurIPS Outstanding Paper Award, Leslie Fox Award, Advisor of SIGIR Best Student Paper Award,
Vice President of Shenzhen Institute of Artificial Intelligence and Robotics for Society, Former Professor
of Georgia Institute of Technology
Research Field: Machine Learning and Applications
蔡小强
CAI, Xiaoqiang
协理副校长
校长讲座教授
Associate Vice President,
Presidential Chair Professor
清华大学博士
国际系统与控制科学院院士、亚太人工智能学会AAIA会士、香港工程师学会会士、全球Top
2%顶尖科学家、国家杰出青年科学基金（海外类）获得者
研究领域：工业与系统工程、运筹学、供应链与物流管理
Ph.D., Tsinghua University
Experience: Academician of the International Academy for Systems and Cybernetic Sciences, AAIA
Fellow, HKIE Fellow, World’s Top 2% Scientists, The National Science Foundation for Distinguished
Young Scholars (Overseas)
Research Field: Industrial and Systems Engineering, Operations Research, Logistics and Supply
Chain Management Science
丁宏强
DING, Hongqiang Chris
校长讲座教授
Presidential Chair Professor
哥伦比亚大学博士
全球前0.1%顶尖科学家、全球前1000位计算机科学和电子领域顶级科学家、全世界计算机领域
Top 400高被引学者，曾获NASA团体成就奖、ICDM/ICMLA/ECML/ISUG最佳论文奖，曾发
表美国《 Science(科学)》杂志封面文章，原德克萨斯大学阿灵顿分校终身教授、原劳伦斯伯克
利国家实验室计算机科学家
研究领域：机器学习、数据挖掘、生物信息学、信息检索、网络链接分析、高性能计算
Ph.D., Columbia University
Experience: World’s Top 0.1% Scientists, Top 1000 Scientists in Computer Science and Electronics,
Top 400 World Highly Cited Researchers in Computer Science, NASA Group Achievement Award,
Best Paper Award of ICDM/ ICMLA/ECML/ISUG, Author of Science Magazine cover story, Former Full
Professor with Tenure at University of Texas at Arlington, Former Computer Scientist at the Lawrence
Berkeley National Laboratory
Research Field: Machine Learning, Data Mining, Bioinformatics, Information Retrieval, Web Link
Analysis, High Performance Computing
sds.cuhk.edu.cn 07
黄铠
HWANG, Kai
校长讲座教授
Presidential Chair Professor
加利福尼亚大学伯克利分校博士
国际电气与电子工程师学会终身会士、亚太人工智能学会AAIA会士、全球Top 2%顶尖科学
家、全球前1000位计算机科学和电子领域顶级科学家、中国科学院云计算中心的首席专家、
深圳市人工智能与机器人研究院中心主任，曾获“建国70年70人科技创新成就奖”，原南加
利福尼亚大学教授
研究领域：计算机体系结构、并行处理、网络安全、云计算和物联网
Ph.D., University of California at Berkeley
Experience: IEEE Life Fellow, AAIA Fellow, World’s Top 2% Scientists, Top 1000 Scientists in
Computer Science and Electronics, Chief Scientist at the Cloud Computing Center, Chinese Academy
of Sciences, Director of Shenzhen Institute of Artificial Intelligence and Robotics for Society, Scientific
Innovation Award among the Top 70 Scientists, Former Professor at University of Southern California
Research Field: Computer Architecture, Parallel Processing, Network Security, Cloud Computing and IoT
COURCOUBETIS,
Konstantinos
校长讲座教授
Presidential Chair Professor
加利福尼亚大学伯克利分校博士
全球Top 2%顶尖科学家、希腊前336最具影响力科学家、IEEE计算机科学逻辑研讨会Test-ofTime奖、雅典经济与商业大学EMBA最佳教学奖、INFORMS MSOM分会“运营管理方向最佳管
理科学论文奖” 、2021年MSOM服务管理方向最佳论文奖、原新加坡科技设计大学教授
研究领域：网络和互联网技术的经济学与行为分析、共享经济和移动性、监管政策、智能电网和
能源系统、资源共享和拍卖
Ph.D., University of California at Berkeley
Experience: World’s Top 2% Scientists, Listed in the 336 Most-cited Greek Scientists, LICS Testof-Time Award, Best Teaching Award for EMBA at Athens University of Economics and Business,
Management Science Best Paper Award in Operations Management from the INFORMS MSOM,
2021 MSOM Service Management Special Interest Group Best Paper Award, Former Professor at
Singapore University of Technology and Design
Research Field: Economics and Performance Analysis of Networks and Internet Technologies, Sharing
Economy and Mobility, Regulation Policy, Smart Grids and Energy Systems, Resource Sharing and Auctions
张大鹏
ZHANG, Dapeng David
校长学勤讲座教授
X.Q. Deng Presidential
Chair Professor
哈尔滨工业大学、滑铁卢大学博士
加拿大皇家科学院院士、加拿大工程院院士、国际电气与电子工程师学会终身会士、国际模式识
别协会会士、亚太人工智能学会AAIA会士、全球Top 2%顶尖科学家、全球前1000位计算机科
学和电子领域顶级科学家、国际图像和图形学报和Springer国际生物识别丛书创始人/主编，曾获
中韩发明金奖及特殊金奖、日内瓦发明展银奖、“裘槎优秀科研者”奖，连续8年（2014-2021
年）Clarivate Analytics全球高被引科学家、深圳市人工智能与机器人研究院中心主任
研究领域：模式识别、图像处理、生物特征识别
Ph.D., Harbin Institute of Technology, University of Waterloo
Experience: Fellow of the Royal Society of Canada, Fellow of Canadian Academy of Engineering, IEEE Life
Fellow, IAPR Fellow, AAIA Fellow, World’s Top 2% Scientists, Top 1000 Scientists in Computer Science and
Electronics, Founder and Editor-in-Chief in International Journal of Image & Graphics (IJIG) and Springer
International Series on Biometrics (KISB), The Gold and Special Gold Awards for Inventions awarded
by China and South Korea, The Silver Award at the Geneva Invention Exhibition and The \"Chroucher
Foundation Outstanding Researcher\" Award, Highly Cited Researchers in Engineering by Clarivate Analytics
(2014-2021), Executive President of Shenzhen Institute of Artificial Intelligence and Robotics for Society
Research Field: Pattern Recognition, Image Processing and Biometrics
黄建华
Faculty
HUANG, Jianhua
副院长
（教员事务及学院战略发展运营）
校长讲座教授
Associate Dean (Faculty Affairs
and Strategic Operations),
Presidential Chair Professor
加利福尼亚大学伯克利分校博士
美国统计协会及国际数理统计学会资深会员、全球Top 2%顶尖科学家、全球前2%高被引统计学
家、国际统计学会会员，INFORMS 2022 影响力奖，原Texas A&M大学统计系代理系主任及数
据科学研究所副所长，入职前为Texas A&M大学终身教授及Arseven/Mitchell讲席教授
研究领域：统计学习、大数据分析及计算、非参数和半参数统计模型及推断、函数型数据和纵向数据分
析、时空数据分析、贝叶斯统计、统计学与自然科学、社会科学、工程、商业等领域的交叉科学研究
Ph.D., University of California at Berkeley
Experience: ASA Fellow, IMS Fellow, World’s Top 2% Scientists, Top 2% Most Cited Statisticians around
the World, ISI Elected Member, the 2022 INFORMS Impact Prize, Former Interim Department Head of
Statistics Department and Associate Director of Institute of Data Science in Texas A&M University, Texas
A&M University Professor and Arseven/Mitchell Chair Professor before joining CUHK-Shenzhen
Research Field: Computational and Bayesian statistics, Functional and Longitudinal Data Analysis,
Nonparametric Statistics, Semi-parametric Inference, Statistical Machine Learning, Statistical Methods for Big
Data Sets, Spatial Statistics, Statistics Applications in Business, Social and Natural Sciences, and Engineering
Faculty
钟叶青
CHUNG, Yeh-Ching
教授
Professor
雪城大学博士
台湾格网计算学会创建者，曾获IEEE ICPADS 2011最佳论文奖、ACM VEE 2016杰出论文
奖、IEEE SC2 2017最佳论文奖、IEEE ICASI 2017最佳论文奖，原台湾清华大学教授，
曾任深圳清华大学研究院云计算与容灾技术实验室副主任
研究领域：云雾计算、大数据、嵌入式系统、并行与分布式系统
Ph.D., Syracuse University
Experience: Founder of Taiwan Association of Grid Computing, Best Paper Award at IEEE ICPADS (2011),
IEEE SC2 (2017), IEEE ICASI (2017), Outstanding Paper Award at ACM VEE (2016), Former Professor
of National Tsing Hua University, Former Deputy Director of Laboratory of Cloud Computing and Disaster
Recovery Technology at Research Institute of Tsinghua University in Shenzhen
Research Field: Cloud-Fog Computing, Big Data, Embedded Systems, Parallel and Distributed Systems
于天维
YU, Tianwei
副院长（学生事务）
教授
Associate Dean
(Student Affairs),
Professor
加利福尼亚大学洛杉矶分校博士
曾获中国教育部科学研究优秀成果奖，国际学术期刊Biology、Scientific Reports、
Current Metabolomics编委，曾任Frontiers in Genetics期刊编委，原美国埃默里大学终身教授
研究领域：生物信息学、统计学、机器学习
Ph.D., University of California, Los Angeles
Experience: China‘s Ministry of Education Prize for Excellent Achievement in Scientific Research,
Editorial Board Member of Biology, Associate Editor for Scientific Reports and Current Metabolomics,
Former Associate Editor for Frontiers in Genetics, Former Professor with Tenure at Emory University
Research Field: Bioinformatics, Statistics, Machine Learning
08 School of Data Science
张寅
ZHANG, Yin
校长讲座教授
Presidential Chair Professor
纽约州立大学石溪分校博士
美国工业与应用数学学会会士、全球Top 2%顶尖科学家，曾获INFORMS运筹学与计算机科学
交叉学科卓越研究奖、国际数学优化学会Paul Y. Tseng纪念奖、JORSC首届优秀论文奖，美国
莱斯大学正教授（退休）
研究领域：最优化算法的设计分析以及数值实现、最优化算法在各领域的应用，特别是在数据科
学、图像与信号处理、机器学习等领域的应用
Ph.D., The State University of New York at Stony Brook
Experience: SIAM Fellow, World’s Top 2% Scientists, The ICS Prize for Research Excellence in the
Interface Between Operations Research and Computer Science, MOS Paul Y. Tseng Memorial Lectureship
in Continuous Optimization, JORSC First Excellent Paper Award, Full Professor at Rice University (Retired)
Research Field: Numerical Optimization, Algorithm Design, Analysis and Implementation, Applications of
Optimization in Various Areas, Particularly in Data Science, Image/Signal Processing and Machine Learning
HAVIV, Moshe
教授
Professor
耶鲁大学博士
以色列运筹研究学会主席，曾获以色列科学基金会资助、昆士兰大学雷布尔德奖学金，
耶路撒冷希伯来大学统计系主任
研究领域：运筹学、排队模型、排队决策和战略行为、马尔可夫决策过程
Ph.D., Yale University
Experience: President of the Israeli Society of Operations Research, Head of Department of Statistics
at Hebrew University of Jerusalem, Israel Science Foundation Grant, The Raybould Fellowship at
University of Queensland
Research Field: Operations Research, Queueing Models, Decision Making and Strategic Behavior in
Queues, Markov Decision Processes
斯坦福大学博士
杉数科技创始人、CTO，曾获国家自然科学基金原创探索计划项目资助，Adobe数字营销研
究奖、CSAMSE最佳论文奖，原明尼苏达大学副教授
研究领域：随机和鲁棒优化、数据驱动决策问题、定价和收益管理
Ph.D., Stanford University
Experience: Co-founder and CTO of Cardinal Operations, Funded by Innovative Exploration Program
of National Natural Science Foundation of China, Adobe Digital Marketing Research Award, CSAMSE
Best Paper Award, Former Associate Professor at University of Minnesota
Research Field: Stochastic and Robust Optimization, Data-Driven Decision-Making, Pricing and
Revenue Management
王子卓
WANG, Zizhuo
副院长（教学）
教授
Associate Dean (Education)
Professor
姚建峰
YAO, Jeff J
校长讲座教授
Presidential Chair Professor
巴黎萨克雷大学（原巴黎第十一大学）博士
美国数理统计学会会士、国际统计学会会员、伯努利数理统计与概率学会理事会成员、
Journal of Multivariate Analysis及Random Matrices: Theory and Applications副主编、
曾任Bernoulli期刊编委，香港大学教授、山东大学数学学院特聘教授
研究领域：随机矩阵理论和高维统计、高维计量经济学模型、马尔可夫链和马尔可夫过程、
时间序列分析、网络数据分析、数字图像分析
Ph.D., Université Paris-Saclay (former Université Paris-Sud Orsay)
Experience: IMS Fellow, ISI Elected Member, Member of the Council of the Bernoulli Society for
Mathematical Statistics and Probability, Associate Editor in Journal of Multivariate Analysis, Random
Matrices: Theory and Applications, Former Associate Editor of Bernoulli, Full Professor of The University of
Hong Kong, Special Guest Professor at the School of Mathematics, Shandong University
Research Field: Random Matrix Theory and High-Dimensional Statistics, High-Dimensional Econometrics Models,
Markov Chains and Markov Processes, Time Series Analysis, Network Data Analysis, Digital Image Analysis
JENTZEN,
Arnulf
校长讲座教授
Presidential Chair Professor
法兰克福大学博士
全球Top 2%顶尖科学家、曾获2018年Joseph F. Traub基于信息复杂性研究的青年研究学家奖、
2022 年“约瑟夫·特劳布奖基于信息复杂性研究成就奖”、菲利克斯克莱因奖，原明斯特大学教授
研究领域：机器学习近似算法、计算随机学、高维偏微分方程的数值分析、随机分析和计算金融
Ph.D., Goethe University Frankfurt
Experience: World’s Top 2% Scientists, 2018 Joseph F. Traub Information-Based Complexity Young
Researcher Award, 2022 Joseph F. Traub Prize for Achievement in Information-Based Complexity,
Felix Klein Prize, Former Professor of the University of Münster
Research Field: Machine Learning Approximation Algorithms, Computational Stochastics,
Numerical Analysis for High Dimensional Partial Differential equations (PDEs), Stochastic Analysis,
Computational Finance
sds.cuhk.edu.cn 09
Faculty
陈天石
CHEN, Tianshi
副教授
Associate Professor
香港中文大学博士
全球Top 2% 顶尖科学家、Automatica 编委、System & Control Letters编委、IEEE控制系统
协会会议编委、2022年深圳市优秀教授称号、第19届IFAC系统识别座谈会全体会议发言人、原
林雪平大学助理教授
研究领域：系统辨识、机器学习、状态推理、数据科学、传感器融合、可扩展算法、非线性控制
Ph.D., The Chinese University of Hong Kong
Experience: World’s Top 2% Scientists, Associate Editor for Automatica, System & Control Letters, IEEE Control
System Society Conference Editorial Board, Shenzhen Excellent Teacher Award 2022, Plenary Speaker for the
19th IFAC Symposium on System Identification, Former Assistant Professor of Linköping University
Research Field: System Identification, Machine Learning, State Inference, Data Science,
Sensor Fusion, Scalable Algorithms, Nonlinear Control
林正人
HAYASHI, Masahito
教授
Professor
京都大学博士
IEEE会士、IMS会士、AAIA会士、 《国际量子信息期刊》编委会成员、深圳国际量子研究院
（SIQA）首席研究科学家，曾任东京大学客座副教授、日本东北大学信息科学研究生院副教授、
名古屋大学数学研究生院正教授、南方科技大学量子科学与工程研究院首席研究科学家，曾获第
12届日本学士院奖、日本学术振兴会JSPS奖、IEEE信息论学会论文奖、日本IBM计算机科学
奖、船井计算机科学信息技术奖
研究领域：量子信息、信息论、统计推断、马尔可夫过程和信息论安全
Ph.D., Kyoto University
Experience: IEEE Fellow, IMS Fellow, AAIA Fellow, Editorial Board of International Journal of Quantum
Information, Visiting Research Professor of Centre for Quantum Technologies, Former Adjunct Associate Professor of
The University of Tokyo, Former Associate Professor of Graduate School of Information Sciences, Tohoku University,
Former Professor of Graduate School of Mathematics, Nagoya University, Former Chief Research Scientist of
Shenzhen Institute for Quantum Science and Engineering, Southern University of Science and Technology, Shenzhen,
12th Japan Academy Medal, JSPS Prize, IEEE Information Theory Society Paper Award, Japan IBM Prize in the
Computer Science Section, Funai Foundation for Information Technology Award in the Computer Science Category Research Field: Quantum Information, Information Theory, Statistical Inference, Markovian Process,
and Information-theoretic Security
茅剑锋
MAO, Jianfeng
助理院长
副教授
数据科学硕士项目联合主任
Assistant Dean,
Associate Professor,
Co-director of M.Sc.
in Data Science Programme
波士顿大学博士
Discrete Event Dynamic Systems: Theory and Applications期刊副编辑，曾获2020
Integrated Communications最佳会议论文奖、Navigation and Surveillance Conference最佳
会议论文奖、2017 IEEE Conference on Automation Science and Engineering最佳会议论
文奖、2020年深圳市优秀教师称号，原南洋理工大学助理教授
研究领域：数据驱动的网络建模与优化、多智能体离散事件动态系统、智能交通与物流系统
Ph.D., Boston University
Experience: Associate Editor of the Journal of Discrete Event Dynamic Systems: Theory and Applications,
2020 Integrated Communications Best Paper Award, Navigation and Surveillance Conference Best Paper
Award, 2017 IEEE Conference on Automation Science and Engineering Best Paper Award, 2020 Shenzhen
Excellent Teacher Award, Former Assistant Professor of Nanyang Technological University
Research Field: Data-Driven Network Modeling and Optimization, Multi-Agent Discrete Event
Dynamic Systems, Smart Transportation and Logistics Systems
方一向
FANG, Yixiang
副教授
Associate Professor
香港大学博士
曾获2021 ACM SIGMOD Research Highlight Award、SIGMOD 2020最佳论文之一、
CCF-B类期刊IPM编委，曾获CCF-华为胡杨林基金资助，曾任新南威尔士大学博士后
研究领域：面向大数据的数据管理、数据挖掘、人工智能
Ph.D., The University of Hong Kong
Experience: 2021 ACM SIGMOD Research Highlight Award, One of the four SIGMOD 2020 Best
Papers, Editorial Board Member of Information Processing & Management, 2022 CCF-Huawei
Populus euphratica Fund, Former Postdoc at The University of New South Wales
Research Field: Data Management, Data Mining, and Artificial Intelligence over Big Data
孙若愚
SUN, Ruoyu
副教授
Associate Professor
明尼苏达大学博士
NeurIPS、ICML、ICLR、AISTATS等人工智能会议领域主席，曾获INFORMS George
Nicolson学生论文竞赛第二名、INFORMS优化协会学生论文竞争荣誉奖，曾任脸书人工智能
研究所全职访问科学家，原伊利诺伊大学香槟分校助理教授
研究领域：深度学习理论和算法、生成模型、大规模优化算法、学习优化、图神经网络、人工
智能在通信网络的应用、通信网络容量理论、通信网络优化算法
Ph.D., University of Minnesota
Experience: Area Chair of NeurIPS, ICML, ICLR, AISTATS and other artificial intelligence conferences, the
2nd place of INFORMS George Nicholson student paper competition, Honorable Mention of INFORMS
optimization society student paper competition, Former Visiting Research Scientist at the Facebook AI
Institute, Former Assistant Professor at the University of Illinois at Urbana-Champaign
Research Field: Deep Learning Theory, Generative Models, Large-scale Optimization, Learning to
Optimize, Graph Neural Nets, AI for Communication, Information Theory, Wireless Communications
刘瑾
LIU, Jin
副教授
Associate Professor
爱荷华大学博士
四次获得新加坡教育部学术研究基金（AcRF Tier 2, PI）、2021年获Duke-NUS颁发的Khoo
Bridge基金奖、2019年获新加坡国立大学数学科学研究所专题项目基金、曾任新加坡国立大学
Duke-NUS医学院（2015-2022）和美国伊利诺伊大学芝加哥分校（2013-2014）终身助理教
授、曾任耶鲁大学博士后（2011-2013）
研究领域：统计遗传、单细胞/空间组学、孟德尔随机、全转录组关联性分析（TWAS）、机器学习
Ph.D., University of Iowa
Experience: Won the Academic Research Fund (AcRF Tier 2, PI) from the Ministry of Education of Singapore
four times, Won the Khoo Bridge Funding Award from Duke-NUS in 2021, Won the Thematic Programs Fund
from the Institute of Mathematical Sciences, National University of Singapore in 2019, Former tenure-track
Assistant Professor at University of Illinois at Chicago, USA (2013-2014) and Duke-NUS Medical School, in the
National University of Singapore (2015-2022), Former postdoc at Yale University (2011-2013)
Research Field: Statistical Genetics, Single-cell/Spatial Omics, Mendelian Randomization (MR),
Transcriptome-wide Association Study (TWAS), Machine Learning
吴保元
WU, Baoyuan
副教授
Associate Professor
中国科学院自动化研究所博士
全球Top 2% 顶尖科学家、深圳市大数据研究院大数据安全计算实验室主任、NeurIPS 2022区
域主席、Neurocomputing期刊编委，曾获国家自然科学基金面上项目资助，曾任腾讯AI Lab
专家研究员
研究领域：人工智能安全隐私、计算机视觉、机器学习与最优化
Ph.D., Pattern Recognition and Intelligent Systems, Chinese Academy of Sciences
Experience: World’s Top 2% Scientists, Director of Big Data Secure Computing Lab at Shenzhen
Research Institute of Big Data, Area Chair of NeurIPS 2022, Associate Editor of Neurocomputing,
Funded by General Program of National Natural Science Foundation of China, Former Principal
Research Scientist in Tencent AI Lab
Research Field: AI Security and Privacy, Machine Learning, Computer Vision and Optimization
10 School of Data Science
陈昕韫
CHEN, Xinyun
助理教授
Assistant Professor
哥伦比亚大学博士
国际著名期刊Operations Research, Annals of Applied Probability, INFORMS Journal of
Computation, Queueing Systems审稿人、美国运筹学和管理学研究协会（INFORMS）应用
概率分会（Applied Probability Society）理事会成员、曾任中国运筹学会金融工程与金融风险管
理分会第四届理事会常务理事(2019-2020)、《Journal of Applied Probability》《Advances
in Applied Probability》副编辑，曾获国家自然科学基金资助，原武汉大学助理教授
研究领域：随机模拟、蒙特卡罗方法、排队论、强化学习
Ph.D., Columbia University
Experience: Reviewer of Operations Research, Annals of Applied Probability, INFORMS Journal
of Computation and Queueing Systems, Editor for Journal of Applied Probability and Advances
of Applied Probability, Council Member of INFORMS Applied Probability (2019-now), Former
Standing Director of Financial Engineering and Financial Risk Management Branch of OR
Society of China, funded by National Science Foundation of China, Former Assistant Professor
at Wuhan University
Research Field: Stochastic Simulation, Monte Carlo Methods, Queueing Models,
Reinforcement Learning
陈逸伦
CHEN, Yilun
助理教授
Assistant Professor
康奈尔大学博士
2018年INFORMS会议金融方向最佳学生论文竞赛入围者，曾获2019年INFORMS会议
Nicholson学生论文竞赛一等奖，原康奈尔大学讲师，曾任哥伦比亚大学博士后
研究领域：应用概率、序列决策、随机最优控制、最优止损与期权定价、老虎机、库存管理
Ph.D., Cornell University
Experience: Finalist of INFORMS 2018 Section on Finance Best Student Paper Competition,
First Place of INFORMS 2019 Nicholson Student Paper Competition, Former Instructor of Cornell
University, Former Postdoc at Columbia University
Research Field: Applied Probability, Sequential Decision-Making, Stochastic Control, Optimal
Stopping and Option Pricing, Multi-armed Bandits, Inventory Control
武执政
WU, Zhizheng
副教授
Associate Professor
李文烨
LI, Wenye
研究副教授
Research Associate Professor
香港中文大学博士
2021年国际人工智能联合会议领域主席，曾获广东省基础与应用基础研究基金自然科学基金面
上项目资助、IEEE-ICAL会议最佳论文奖，曾任香港中文大学和加拿大阿尔伯塔大学博士后
研究领域：机器学习、人工智能、凸优化、概率推理
Ph.D., The Chinese University of Hong Kong
Experience: Area Chair of IJCAI’2021, Funded by Natural Science Foundation of Guangdong Province
General Program, IEEE-ICAL Conferences Best Paper Award, Former Postdoc at The Chinese University
of Hong Kong and University of Alberta
Research Field: Machine Learning, Artificial Intelligence, Convex Optimization,
and Probabilistic Inference
严明
YAN, Ming
副教授
Associate Professor
加州大学洛杉矶分校博士
全球Top 2% 顶尖科学家，曾获2020脸书教授奖（Facebook Faculty Award），曾在密西根
州立大学计算数学、科学与工程系和数学系任助理教授和副教授，曾任莱斯大学计算与应用数
学系和加州大学洛杉矶分校数学系博士后研究员
研究领域：分布式优化，稀疏优化，机器学习，大规模优化算法
Ph.D., University of California, Los Angeles
Experience: World’s Top 2% Scientists, 2020 Facebook Faculty Award, Former Assistant Professor
(tenure-track) and Associate Professor (tenured) in the Department of Computational Mathematics,
Science and Engineering (CMSE) and the Department of Mathematics at Michigan State
University, Former Postdoctoral Scholar and Assistant Adjunct Professor at University of California,
Los Angeles, Former Postdoctoral Fellow in the Department of Computational and Applied
Mathematics at Rice University
Research Field: Distributed Optimization, Sparse Optimization, Machine Learning,
Large-Scale Optimization
南洋理工大学博士
全球Top 2% 顶尖科学家、IEEE语音与语言处理技术委员会委员，现任IEEE/ACM
Transactions on Audio Speech and Language Processing编委，曾获INTERSPEECH
2016最佳学生论文奖、2012亚太信号与信息处理协会年度峰会最佳论文奖，曾在Meta (原
Facebook)、京东、苹果、爱丁堡大学、微软亚洲研究院等机构从事学术研究和技术研发工作
研究领域：语音信息处理、语音生成、深度伪造检测
Ph.D., Nanyang Technological University
Experience: World’s Top 2% Scientists, IEEE Speech and Language Processing Technical Committee
Member, Associate Editor of IEEE/ACM Transactions on Audio Speech and Language Processing,
INTERSPEECH 2016 Best Student Paper award (Recipient: Manu Airaksinen), APSIPA Annual
Submit and Conference 2012 Best Paper award, Worked for Meta (formerly named Facebook),
JD.COM, Apple, University of Edinburgh, and Microsoft Research Asia
Research Field: Speech Processing, Speech Synthesis, DeepFake Detection
吴均峰
WU, Junfeng
副教授
Associate Professor
香港科技大学博士
现任期刊IEEE Transactions on Control of Network Systems编委，曾获中国控制会议
（CCC2015）关肇直奖，原浙江大学教授，曾任瑞典皇家工学院研究员与博士后研究员
研究领域：分布式系统、网络控制系统、卡尔曼滤波、信号处理、信息物理系统安全与隐私
Ph.D., The Hong Kong University of Science and Technology
Experience: Associate Editor of IEEE Transactions on Control of Network Systems, Guan Zhaozhi Best
Paper Award of the 34th China Control Council (CCC 2015), Former Professor at Zhejiang University,
Former Researcher and Former Postdoctoral Researcher at the Royal Institute of Technology
Research Field: Distributed Systems, Control Network Systems, Kalman Filtering, Signal Processing,
Cyber Security and Privacy
sds.cuhk.edu.cn 11
郭振兴
GUO, Zhenxing
助理教授
Assistant Professor
埃默里大学博士
曾获Michael H. Kutner 博士生奖，与临床医生以及生物学家进行密切合作，项目涉及哮喘、癌
症以及阿尔兹海默症
研究领域：生物统计学、统计基因组学、计算生物学
Ph.D., Emory University
Experience: Michael H. KutnerDoctoral Student Award, Collaboration project with clinician and
biologist involves the study of asthma, cancer, and Alzheimer’s disease
Research Field: Biostatistics, Statistical Genomics, and Computational Biology
Faculty
韩俊
HAN, Jun
助理教授
Assistant Professor
圣母大学博士
曾获ACM UbiComp杰出论文奖，曾任IEEE VIS Short Paper 2021和2022程序委员会委员
研究领域：可视化、用户界面与交互、人机交互、深度学习
Ph.D., University of Notre Dame
Experience: Distinguished Paper Award at ACM UbiComp, program committee member at IEEE VIS
Short Paper 2021 and 2022
Research Field: Visualization, User Interface and Interaction, Human-computer Interaction,
Deep Learning
贺品嘉
HE, Pinjia
助理教授
Assistant Professor
香港中文大学博士
全球Top 2% 顶尖科学家、顶会ICSE 2024和ESEC/FSE 2023的程序委员会成员、顶刊
TOSEM副编辑、TSE/ICSE/KDD/IJCAI等多个顶级会议和期刊审稿人，曾获ISSRE会议最
具有影响力论文奖、曾获IEEE开源软件服务奖，曾任苏黎世联邦理工学院博士后
研究领域：软件工程、系统可靠性、自然语言处理、深度学习
Ph.D., The Chinese University of Hong Kong
Experience: World’s Top 2% Scientists, PC Member of ICSE 2024 and ESEC/FSE 2023, Associate Editor
of TOSEM, Reviewer of TSE, ICSE, KDD, IJCAI, Most Influential Paper (26 papers selected in 30 years) of
ISSRE 2019, The First IEEE Open Software Services Award, Former Postdoctoral Scholar at ETH Zurich
Research Field: Software Engineering, System Reliability, Natural Language Processing, Deep Learning
胡桑
HU, Sang
助理教授
Assistant Professor
香港中文大学博士
国际著名期刊Operations Research, Finance and Stochastics, SIAM Journal on Financial
Mathematics审稿人，曾获国家和省级基金，曾发表UTD顶刊论文，曾任新加坡国立大学风险
管理研究所研究员
研究领域：行为金融学、风险管理学
Ph.D., The Chinese University of Hong Kong
Experience: Reviewer of Operations Research, Finance and Stochastics, SIAM Journal on Financial
Mathematics, funded by National and Provincial Funding, papers published by UTD (top journal),
Former Research Fellow at Risk Management Institute at National University of Singapore
Research Field: Behavioral Finance and Risk Management
李爽
LI, Shuang
助理教授
Assistant Professor
佐治亚理工学院博士
曾获INFORMS QSR最佳学生论文竞赛决赛入围奖、INFORMS社交媒体分析最佳学生论文竞
赛决赛入围奖、H. Milton Stewart工业学院研究生贾维斯奖第二名、中国科学技术大学自动化系
优秀本科论文奖，曾任哈佛大学博士后
研究领域：时序数据分析和决策的机器学习方法及其在医疗保健、智慧城市和社交媒体中的应用
Ph.D., Georgia Institute of Technology
Experience: INFORMS QSR Best Student Paper Competition Finalist Award, INFORMS Social Media
Analytics Best Student Paper Competition Finalist Award, Second Place of Jarvis Award for Graduate
Student Research in H. Milton Stewart School of Industrial and Systems Engineering at Georgia
Institute of Technology, Outstanding Undergraduate Thesis of Department of Automation at University
of Science and Technology of China, Former Postdoctoral Fellow at Harvard University
Research Field: Machine Learning for Sequential Data Analysis and Decision-making, Applications to
Healthcare, Smart Cities, and Social Media
高品
GAO, Pin
助理教授
Assistant Professor
香港科技大学博士
曾在顶刊Management Science与Operations Research发表论文，曾任金融科技公司定量分析师
研究领域：收益管理、推荐系统、算法设计、机制设计
Ph.D., The Hong Kong University of Science and Technology
Experience: Papers published by Management Science, Operations Research (top journal),
Former Quantitative Analyst of Fintech company
Research Field: Revenue Management, Recommendation System, Algorithm Design,
Mechanism Design
香港城市大学博士
国际著名期刊Institute of Electrical and Electronics Engineers, Pattern Recognition, SIAM
Journal on Mathematics of Data Science审稿人，曾获香港城市大学杰出学术表现奖，曾任
康奈尔大学博士后研究员
研究领域：机器学习、计算机视觉、最优化、神经科学信号处理和数据分析
Ph.D., City University of Hong Kong
Experience: Reviewer of Institute of Electrical and Electronics Engineers, Pattern Recognition, SIAM
Journal on Mathematics of Data Science, CityU Outstanding Academic Performance Award; Former
Postdoctoral Associate at Cornell University
Research Field: Machine Learning, Computer Vision, Optimization, Neuroscience Signal Processing
and Data Analysis
樊继聪
FAN, Jicong
助理教授
Assistant Professor
12 School of Data Science
西蒙菲莎大学博士
NeurIPS、ICML、ICLR审稿人，曾获MITACS学术训练奖和中国国家奖学金，曾任加拿大滑铁
卢大学博士后和维克特研究院的研究员
研究领域：增强学习，包括基于模型的增强学习、可解释性增强学习、智能体评价和表示学习；
增强学习相关的应用，包括信息提取和体育运动分析
Ph.D., Simon Fraser University
Experience: Reviewer of NeurIPS, ICML, ICLR, etc., MITACS Research Training Award Canada,
National scholarship from China, Former Postdoctoral Fellow at the University of Waterloo, Former
Affiliated Researcher at Vector Institute
Research Field: Reinforcement Learning (RL), including Model-based RL, Interpretable RL, Agent
Evaluation and Representation Learning; RL-relevant Applications, including Information Extraction
and Sports Analytics
刘桂良
LIU, Guiliang
助理教授
Assistant Professor
马晨昊
MA, Chenhao
助理教授
Assistant Professor
香港大学博士
曾任多个顶级期刊（如 TKDE 和 VLDBJ）的审稿人，曾获SIGMOD 2020会议的最佳论文之一
（4/458）、2021 ACM SIGMOD Research Highlight奖
研究领域：大规模数据管理和数据挖掘
Ph.D., The University of Hong Kong
Experience: Former reviewer for top journals such as TKDE and VLDBJ, One of four Best of SIGMOD
2020 (4/458), ACM SIGMOD Research Highlight Award 2021
Research Field: Large-scale Data Management and Data Mining
哥伦比亚大学博士
国际著名期刊Operations Research审稿人，曾任哥伦比亚大学助教
研究领域：匹配市场设计、供应链管理、客户关系管理
Ph.D., Columbia University
Experience: Former Reviewer of Operations Research, Former Teaching Assistant at
Columbia University
Research Field: Analysis and Design of Large Matching Markets, Supply Chain Management
and Customer Relationship Management
鲁家琦
LU, Jiaqi
助理教授
Assistant Professor
李兆媛
LI, Zhaoyuan
助理教授
Assistant Professor
香港大学博士
曾获CCF-腾讯犀牛鸟基金资助，曾任香港大学经济及工商管理学院博士后和兼职讲师
研究领域：高维统计、随机矩阵、统计方法应用、机器学习、金融科技
Ph.D., The University of Hong Kong
Experience: Funded by CCF-Tencent Rhino Bird Fund; Post-doctoral Fellow and part-time Lecturer
at Faculty of Business and Economics, The University of Hong Kong
Research Field: High-dimensional Statistics, Random Matrix Theory, Applications of Statistical
Methods, Machine Learning, Financial Technology
程高木
LOUART, Cosme
助理教授
Assistant Professor
格勒诺布尔-阿尔卑斯大学博士
曾在EDF（法国电力公司）北京研发中心担任数据工程师，在数学和机器学习期刊
（ICML、AISTATS、IEEE、Annals of Applied Probability）上发表多篇文章
研究领域：高维数据处理应用数学、机器学习
Ph.D., University of Grenoble Alpes
Experience: Worked as a Data Engineer in the Beijing R&D Center of EDF (French Electricity
Company), Published several articles in mathematics and machine learning journals (ICML, AISTATS,
IEEE, Annals of Applied Probability)
Research Field: Applied Mathematics for High Dimensional Data Processing, Machine Learning
李肖
LI, Xiao
助理教授
Assistant Professor
香港中文大学博士
国际著名期刊Journal of Machine Learning Research, IEEE Transactions on Signal
Processing, NeurIPS, ICLR审稿人，论文曾发表在2019神经信息处理系统大会NeurIPS（排名
前3%）、2020国际学习表征会议（排名前1.85%）、国际性学术刊物如SIAM优化期刊、SIAM
成像科学期刊、IEEE图像处理汇刊，曾任香港中文大学助教
研究领域：数学优化（非光滑、非凸以及随机优化）、机器学习、信号处理
Ph.D., The Chinese University of Hong Kong
Experience: Reviewer of Journal of Machine Learning Research, IEEE Transactions on Signal
Processing, NeurIPS, ICLR, Paper published by Neural Information Processing Systems (NeurIPS
2019, Spotlight, Top 3%), International Conference on Learning Representation (ICLR 2020, Oral,
Top 1.85%), SIAM Journal on Optimization, SIAM Journal on Imaging Sciences, IEEE Transactions
on Image Processing, Former Teaching Assistant at The Chinese University of Hong Kong
Research Field: Continuous Optimizatin (Nonsmooth, Nonconvex, Stochastic), and with Applications
to Machine Learning and Signal Processing
李彤欣
LI, Tongxin
助理教授
Assistant Professor
加州理工学院博士
曾获2022年SIGEnergy博士论文奖荣誉奖，曾获Resnick可持续发展中心2021影响力资助奖，
曾两次任亚马逊云计算安全组实习应用科学家，曾参与可再生能源实验室、帕萨迪纳市水电局以
及加州理工学院能源设施中心多个电力系统优化设计合作项目
研究领域：可信机器学习、在线学习、智能电网、电力系统与控制
Ph.D., California Institute of Technology
Experience: 2022 SIGEnergy Doctoral Dissertation Award Honorable Mention, Recipient of the 2021
Impact Grants from the Resnick Sustainability Institute, Applied Scientist at AWS Security (Intern, two
times), Participated in various projects on power systems in collaboration with NREL, Pasadena Water
and Power, and Caltech Facilities
Research Field: Trustworthy Machine Learning, Online Learning, Power Systems, Smart Grid and Control
sds.cuhk.edu.cn 13
Faculty
Associate Professor
王趵翔
WANG, Baoxiang
助理教授
Assistant Professor
香港中文大学博士
国际著名期刊ICML, NeurIPS, ICLR, Pattern Recognition审稿人，曾任加拿大皇家银行研究
所研究员
研究领域：强化学习、在线学习和学习理论
Ph.D., The Chinese University of Hong Kong
Experience: Reviewer of ICML, NeurIPS, ICLR, Pattern Recognition, Former Student Research
Scientist at Royal Bank of Canada Research Institute
Research Field: Reinforcement Learning, Online Learning and Learning Theory
谢李岩
XIE, Liyan
助理教授
Assistant Professor
佐治亚理工学院博士
曾入围2019年INFORMS会议QSR方向最佳学生论文奖，曾入围2020年伯克利大学EECS
领域“女性学术新星”、曾获2020年佐治亚理工学院IDEaS-TRIAD和ARC-TRIAD奖学金，
曾任佐治亚理工学院讲师
研究领域：基于传感器网络及卫生保健的数据科学研究、序贯变化检测、鲁棒优化
Ph.D., Georgia Institute of Technology
Experience: Finalist of INFORMS QSR Best Student Paper Award 2019; participated in EECS Rising
Stars Workshop 2020; IDEaS-TRIAD Research Fellowship and ARC-TRIAD Fellowship, Georgia
Institute of Technology 2020; Former Instructor at Georgia Institute of Technology
Research Field: Theoretical and Methodological Foundations of Data Science Inspired by Important
Applications (Sensor Networks and Health Care), with a particular interest in Sequential Change
Detection and Robust Hypothesis Test through the Lens of Robust Optimization
意大利帕多瓦大学博士
曾获2022年华为火花奖、曾获NLPCC 2022最佳论文奖、曾获NAACL 2019最佳可解释NLP论
文、SIGIR 2017最佳论文提名奖、玛丽居里奖学金，长期担任ICLR/NeurIPS/ICML审稿人
研究领域：自然语言处理、信息检索、应用机器学习
Ph.D., University of Padua
Experience: Huawei Spark Award 2022, Best Paper Award in NLPCC 2022, Best Explainable NLP
Paper in NAACL 2019, Best Paper Nomination Award in SIGIR 2017, Marie Curie Fellowship, Reviewer
of ICLR, NeurIPS and ICML
Research Field: Natural Language Processing (NLP), Information Retrieval, Applied Machine
Learning, Quantum Machine Learning
王本友
WANG, Benyou
助理教授
Assistant Professor
弗吉尼亚大学博士
曾获国家自然科学基金青年科学基金资助，曾任波士顿大学和弗洛里达大学博士后研究员、
亚利桑那州立大学博士后
研究领域：分布式优化、机器学习、多智能体网络
Ph.D., University of Virginia
Experience: Funded by Youth Program of National Natural Science Foundation of China, Former
Postdoctoral Associate at Boston University and University of Florida, Former Postdoctoral Scholar
at Arizona State University
Research Field: Distributed Optimization, Machine Learning, Multi-agent Networks
濮实
PU, Shi
助理教授
Assistant Professor
阿卜杜拉国王科技大学博士
点昀技术创始人
研究领域：计算成像、光学、深度/超快速成像、基于物理学的渲染与仿真、深度学习、优化
Ph.D., King Abdullah University of Science and Technology
Experience: Founder of Point Spread Technology
Research Field: Computational Photography, Optics, Depth/Transient Imaging, Physical Based
Rendering and Simulation, Deep Learning, Optimization
香港中文大学博士
加拿大统计杂志《复杂性评论》审稿人
研究领域：贝叶斯统计、统计基因组学、统计计算和大数据分析
Ph.D., The Chinese University of Hong Kong
Experience: Reviewer for Complexity, The Canadian Journal of Statistics
Research Field: Bayesian Statistics, Statistical Genomics, Statistical Computing,
and Big Data Analysis
孙启霖
SUN, Qilin
助理教授
Assistant Professor
宋方达
SONG, Fangda
助理教授（定期聘任）
Assistant Professor
(Fixed Term)
MILZAREK,
Andre
助理教授
Assistant Professor
慕尼黑工业大学博士
曾获国家自然科学基金外国青年学者研究基金资助、曾任北京大学博士后
研究领域：非光滑优化、大规模随机优化、二阶方法和理论
Ph.D., Technical University of Munich
Experience: Funded by International Young Scientists project of National Natural Science
Foundation of China, Former Postdoct at Peking University
Research Field: Nonsmooth Optimization, Large-scale and Stochastic Optimization,
Second Order Methods and Theory
14 School of Data Science
华中科技大学博士
第十二届EAI网络与社区发展国际会议网络主席、第七届云计算国际会议本地主席，
曾发表30多篇论文（4篇IEEE Trans./Journal），谷歌学术引用达700多次
研究领域：数据驱动的通信、边缘计算和物联网
Ph.D., Huazhong University of Science and Technology
Experience: Web Chair for 12th EAI International Conference for the Development of Networks
& Communities, Local Chair for 7th International Conference on Cloud Computing, 30+ paper
published (4 by IEEE Trans./Journal), 700+ academic citations from Google
Research Field: Data-driven Communications, Edge Computing, and Internet of Things
缪一铭
MIAO, Yiming
研究助理教授
Research Assistant Professor
加利福尼亚大学圣迭戈分校博士
曾任 Journal of Time Series Analysis 杂志审稿人
研究领域：时间序列分析、重抽样方法、高维数据分析及无参数统计
Ph.D., University of California San Diego
Experience: Former Reviewer for Journal of Time Series Analysis
Research Field: Time Series Analysis, Resampling and Bootstrap Method, High-dimensional
Data Analysis and Nonparametric Statistics
张云翼
ZHANG, Yunyi
助理教授
Assistant Professor
* 学术休假中 On academic leave
亚利桑那州立大学博士
曾获亚利桑那州立大学工程研究生奖学金，曾任亚利桑那州立大学助教、飞利浦医疗算法工程师
研究领域：机器学习、组合问题优化、图学习和优化、循环神经网络、行列式点过程
Ph.D., Arizona State University
Experience: Engineering Graduate Fellowship at Arizona State University, Former Teaching Assistant
at Arizona State University, Former Algorithm Engineer in Philips Healthcare
Research Field: Machine Learning, Optimization of Combinatorial Problems, Optimization and
Learning of Graph, RNNs and Determinantal Point Process
于天舒
YU, Tianshu
助理教授
Assistant Professor
杜克大学博士
国际著名期刊Management Science、INFORMS Journal on Computing审稿人，
曾任哥伦比亚大学博士后
研究领域：近似动态规划、随机模型
Ph.D., Duke University
Experience: Reviewer for Management Science and INFORMS Journal on Computing,
Former postdoctoral research scholar at Columbia University
Research Field: Approximate Dynamic Programming, Stochastic Modeling
张经纬
ZHANG, Jingwei
助理教授
Assistant Professor
香港科技大学博士
曾提名香港科技大学第八届香港生产与运营管理协会国际会议最佳学生论文奖荣誉，曾任香港
科技大学工业工程及決策分析学系博士后研究员
研究领域：数据驱动的排队网络、在线算法设计、供应链管理和应用
Ph.D., The Hong Kong University of Science and Technology
Experience: Honorable Mention at the 8th POMS-HK International Conference Best Student Paper
Competition, The Hong Kong University of Science and Technology (HKUST); Former Postdoctoral
Fellow at the Department of IEDA, HKUST
Research Field: Data-Driven Queuing Networks, Online Algorithm Design, Supply Chain
Management and Applications
张海伦
ZHANG, Hailun
助理教授
Assistant Professor
西北大学博士
曾获Nemhausser最佳学生论文奖，曾任西北大学助教
研究领域：服务系统运营、排队论、供应链管理、最优控制、马氏决策过程、应用概率、机器学习
Ph.D., Northwestern University
Experience: Nemhausser’s Best Student Dissertation Prize, Former Teaching Assistant
at Northwestern University
Research Field: Service Operations, Queueing, Supply Chain Management, Optimal Control,
Markovian Decision Process, Applied Probability, Machine Learning
于伦
YU, Lun
助理教授
Assistant Professor
西北大学博士
著名国际期刊Mathematical Programming, Naval Research Logistics, Electric Power
Systems Research审稿人，曾任美国洛斯阿拉莫斯国家实验室博士后研究员
研究领域：不确定性下的优化、整数规划、能源系统
Ph.D., Northwestern University
Experience: Reviewer of Mathematical Programming, Naval Research Logistics, Electric Power
Systems Research, Former Postdoctoral Research Associate at Los Alamos National Laboratory
Research Field: Optimization under Uncertainty, Integer Programming, Energy Systems
杨浩翔
YANG, Haoxiang
助理教授
Assistant Professor
sds.cuhk.edu.cn 15
贾建民
JIA, Jianmin
校长讲座教授（特聘）
Presidential Chair Professor
(by courtesy)
德克萨斯大学奥斯汀分校博士
《运筹学》副主编、美国营销科学研究学会学术董事、中国市场学会学术委员会副主任
研究领域：大数据行为研究、社交网络、决策分析、感知风险
Ph.D., The University of Texas at Austin
Experience: Associate Editor of Operations Research, Academic Trustee of Marketing Science Institute
(USA), Vice Chairman of the Academic Committee of China Marketing Association
Research Field: Big Data Behavioral Research, Social Networks, Decision Making, Perceptions of Risk
MANDELBAUM,
Avishai
教授（短期特邀）
Professor (Fractional)
康奈尔大学博士
运筹学和管理科学协会会士、制造业与服务业经营管理协会会士、以色列理工学院服务企业工程
实验室联合创建者，曾获Technion Yanai学术教育卓越奖、Technion Taub学术卓越奖、就职
服务研究创新奖
研究领域：随机网络、概率和随机过程、统计、数学编程、控制理论、服务系统（医院、呼叫中
心、银行）
Ph.D., Cornell University
Experience: INFORMS Fellow, MSOM Fellow, Co-founder of the Technion Service Enterprise Engineering
Laboratory, Technion's Yanai Prize, Technion Taub Prize, Inaugural Service Research Innovation Award
Research Field: Stochastic Networks, Probability and Stochastic Processes, Statistics, Mathematical
Programming, Control Theory, Service Systems (hospitals, contact centers, banks)
赵建良
ZHAO, Jianliang Leon
加利福尼亚大学伯克利分校博士
原香港城市大学信息系统讲座教授，曾任香港城市大学信息系统系主任
研究领域：金融科技、区块链技术和业务应用、商业中的大数据应用、工作流技术与管理
Ph.D., University of California at Berkeley
Experience: Former Chair Professor and Former Head of Information Systems at City University of
Hong Kong
Research Field: FinTech, Blockchain Technology and Business Applications, Big Data Applications
in Business, Workflow Technology and Management
Faculty
中山大学博士
深圳市大数据研究院研究科学家、国际著名期刊和会议（International Journal of Computer
Vision, Neural Information Processing Systems）审稿人，曾获Google YouTube大规模视
频挑战赛金牌，ESI高被引论文，曾任商汤研究院深度学习核心技术组高级研究员
研究领域：计算机视觉、深度学习
Ph.D., Sun Yat-sen University
Experience: Research Scientist at the Shenzhen Research Institute of Big Data, Reviewer of
International Journal of Computer Vision, Neural Information Processing Systems, Google YouTube
8M Video Understanding Challenge (Golden Metal), ESI highly cited paper, Former Senior Researcher
at the SenseTime Research, Shenzhen
Research Field: Computer Vision and Deep Learning
张瑞茂
ZHANG, Ruimao
研究助理教授
Research Assistant Professor
香港中文大学博士
曾任国际对冲基金千禧年资本中国区子公司世坤投资咨询有限公司、前海人寿保险资产管理部门以
及平安保险集团总部风险管理部门量化投资研究员与量化建模研究员
研究领域：离散数学与算法设计、运筹优化、应用数学建模与算法设计
Ph.D., The Chinese University of Hong Kong
Experience: Quantitative Researcher at WorldQuant LLC, Capital Management Department of
Qian Hai Life Insurance Co., Ltd., and Scientific Modeling Researcher at the Risk Management
Department of Ping An Insurance (Group) Company of China, Ltd.
Research Field: Discrete Mathematics and Algorithm Design, Operations Research,
Applied Mathematics in Modeling and Algorithm Design
吕伯君
LU, Bojun
助理教授（教学）
Assistant Professor
(Teaching)
斯坦福大学博士
国际电气与电子工程师学会会士、未来智联网络研究院院长、深圳市大数据研究院常务副院长、
香港中文大学（深圳）-京东集团人工智能联合实验室主任
研究领域：数据分析和信息系统
Ph.D., Stanford University
Experience: IEEE Fellow, Director of Future Network of Intelligence Institute, Executive Vice Director
of Shenzhen Research Institute of Big Data, Director of CUHK(SZ)-JD Joint AI Lab
Research Field: Data Analytics and Information System
崔曙光
CUI, Shuguang
校长学勤讲座教授（特聘）
X.Q. Deng Presidential
Chair Professor (by courtesy)
曾家炜
TSANG, Ka Wai
研究助理教授
Research Assistant Professor
斯坦福大学博士
曾获国家自然科学基金青年项目资助，曾任斯坦福大学访问讲师、International Conference
on Conceptual程序委员会会员
研究领域：计算数学、金融工程与数据分析、机器学习与时间序列分析
Ph.D., Stanford University
Experience: Funded by Youth Program of National Natural Science Foundation of China, Former
Visiting Instructor of Stanford University, Former PC member of International Conference on Conceptual
Research Field: Computational Mathematics, Financial Engineering and Data Analytics, Machine
Learning and Time Series Analysis
校长讲座教授（特聘）
Presidential Chair Professor
(by courtesy)
16 School of Data Science
季统凯
JI,Tongkai
教授（客座）
Professor (Adjunct)
中国科学院大学博士（原中国科学院研究生院）
中国科学院云计算中心主任、中国信息化专家委员会专家、中国云计算专家委员会委员、中国大
数据专家委员会专家，曾获吴文俊人工智能自然科学奖二等奖、第十八届及十九届中国专利优秀
奖、中国产学研合作创新奖、中国科学院院地合作奖先进个人（科技类）一等奖、全军科技进步
二等奖、广东省科技进步二等奖
研究领域：云计算操作系统、大数据应用、遥感多元信息融合和高分率影像重构
Ph.D., University of Chinese Academy of Sciences
Experience: Director of Chinese Academy of Cloud Computing Industry Technology Innovation
and Incubation Center, Expert of China Informatization Expert Committee, Member of China Cloud
Computing Expert Committee, Expert of China Big Data Expert Committee, The 2nd prize of the 10th
Wu Wenjun Artificial Intelligence Natural Science Award, Winner of the 18th and the 19th China
Patent Excellence Award, 2010 China Industry and Research Cooperation Innovation Award, First
Prize of Advanced Individual (Science and Technology) Award of the 2009 Chinese Academy of
Sciences, the 2nd Prize of Science and Technology Progress of the Whole Army, Guangdong Province
Science and Technology Progress 2nd Prize
Research Field: Cloud Computing OS, Big Data, Multi-information Fusion and Super-Resolution
Image Reconstruction
里海大学博士
全球Top 2%顶尖科学家、全球前1000位计算机科学和电子领域顶级科学家、国际电气与电子工程师
学会会士、国际欧亚科学院院士，曾任微软亚洲研究院副院长与科大讯飞副总裁兼研究院联席院长
研究领域：图像/视频信号处理、分析、编码、传输和通信，多媒体内容分析和搜索，机器学习和
人工智能，计算机视觉
Ph.D., Lehigh University
Experience: World’s Top 2% Scientists, Top 1000 Scientists in Computer Science and Electronics,
IEEE Fellow, IEAS Academician, Co-Founder/Principal Researcher/Research Area Manager of Microsoft
Research, Corporate VP and Co-President of Research in iFlytek
Research Field: Image/Video Processing, Analysis, Coding, Streaming and Communications;
Multimedia Content Analysis and Search; Machine-learning and AI; Computer Vision
李世鹏
LI, Shipeng
教授 （客座）
Professor (Adjunct)
佐治亚理工学院博士
Facebook iOS优化首席工程师
研究领域：随机算法、应用概率、统计物理学中的相变、社交网络、金融市场的定量分析
Ph.D., Georgia Institute of Technology
Experience: Lead Engineer for Facebook iOS main app
Research Field: Randomized Algorithms, Applied Probability, Phase Transitions in Statistical Physics,
Social Network, Quantitative Analysis on Financial Markets
杨林骥
YANG, Linji
专业应用副教授
（短期特邀）
Associate Professor of
Practice (Fractional)
哥伦比亚大学博士
香港中文大学系统工程与工程管理学系教授、香港中文大学（深圳）金融工程理学硕士项目主任
研究领域：计量金融及风险、蒙特卡罗模拟、应用概率
Ph.D., Columbia University
Experience: Director of Engineering Program in Financial Technology and Deputy Director of Master
of Science Program in Financial Engineering at The Chinese University of Hong Kong
Research Field: Quantitative Methods in Finance and Risk, Monte Carlo Simulation,
Applied Probability
陈南
CHEN, Nan
教授（客座）
Professor (Adjunct)
国立巴黎高等矿业学校博士
上海交通大学安泰经济与管理学院校特聘教授（退休），曾获首届中国管理学一等奖、中国改革
开放30周年物流杰出奖与中国改革开放40周年物流杰出奖，曾任上海交通大学中美物流研究院院
长、中国学位委员会学科评议组成员和中国自然科学基金委评委
研究领域：最优化与均衡、数字供应链与智能物流、交通科学、平台经济与管理
Ph.D., Ecole National des Mines de Paris
Experience: Distinguished Professor at Antai College of Economy and Management (retired), Excellent
Prize for Management (First Prize) of China, Excellent Prize of Logistics for thirty years in China and
Excellent Prize of Logistics for forty years in China, Former Dean of Sino-US Global logistics Institute
at Shanghai Jiao Tong University, Former Member of Management Science Group of Academic
Committee of State Council of China, Former Panel member of National Science Foundation of China
Research Field: Optimization and Equilibrium, Digital Supply Chain and Smart Logistics,
Transportation Science, Platform Economics and Management
朱道立
ZHU, Daoli
教授 （短期特邀）
Professor (Fractional)
MIYAZAWA,
Masakiyo
教授（短期特邀）
Professor (Fractional)
日本东京工业大学博士
东京理科大学教授
研究领域：随机网络、排队理论、应用概率、渐近分析
Ph.D., Tokyo Institute of Technology
Experience: Professor at Tokyo University of Science
Research Field: Stochastic Network, Queueing theory, Applied Probability, Asymptotic Analysis
宗成庆
ZONG, Chengqing
教授 （客座）
Professor (Adjunct)
中国科学院计算技术研究所博士
国际计算语言学委员会委员、亚洲自然语言处理学会主席、国际期刊 ACM TALLIP 副主编、
IEEE Intelligent Systems 编委，曾获中国科学院优秀导师奖、北京市优秀教师、
国家科技进步奖二等奖，曾任顶级国际会议 ACL-IJCNLP 2015 程序委员会主席和
ACL-IJCNLP 2021大会主席、AAAI、IJCAI和COLING等一流国际会议的领域主席、
资深领域主席或程序委员会主席，原模式识别国家重点实验室副主任
研究领域：自然语言处理，机器翻译，文本数据挖掘，人机对话系统，语言认知计算
Ph.D., Institute of Computing Technology, Chinese Academy of Sciences
Experience: Member of ICCL, President of AFNLP, Associate Editor of ACM TALLIP, Editorial Board
Member of IEEE Intelligent Systems, the Outstanding Supervisor Prize of the Chinese Academy of
Sciences, the honorary title of Outstanding Teacher awarded by the Beijing Municipal Government, 2nd
Prize of the State Preeminent Science and Technology Award of China, Programming Committee Cochair of the ACL-IJCNLP 2015 conference, General Conference Chair of ACL-IJCNLP 2021, Senior Area
Chair/Area Chair or Programming Committee Co-chair of AAAI, IJCAI, COLING, etc., Former Deputy
Director of the National Laboratory of Pattern Recognition
Research Field: Natural Language Processing, Machine Translation, Text Data Mining, Humancomputer Dialogue System, Linguistic Cognitive Computing *注：师资信息持续更新，此版本更新至2023年6月
Note: Faculty info was updated in June 2023 and is continuously updated
罗效东
LUO, Xiaodong
专业应用教授（客座）
Professor of Practice
(Adjunct)
李锦兴
LI, Jinxing
助理教授（客座）
Assistant Professor
(Adjunct)
万翔
WAN, Xiang
副教授（客座）
Associate Professor
(Adjunct)
麻省理工学院博士
曾任麻省理工学院博士后研究员
研究领域：配对优化器的原对偶子问题列生成方法，民航运营恢复、定价及收益管理，
连续线性程序，生产制造系统算法，应用统计，组合优化
Ph.D., Massachusetts Institute of Technology
Experience: Former Postdoctoral Research Fellow at Massachusetts Institute of Technology
Research Field: The Primal-dual Subproblem Column Generation Approach for the Pairing Optimizer,
Airline Operations Recovery/Pricing and Revenue Management, Continuous Linear Programs,
Algorithms for Manufacturing Systems, Applied Statistics, Combinatorial Optimization
香港理工大学博士
曾任香港中文大学（深圳）博士后
研究领域：模式识别、图像处理、生物特征识别、多模态学习、深度哈希学习
Ph.D., The Hong Kong Polytechnic University
Experience: Former Postdoc at The Chinese University of Hong Kong, Shenzhen
Research Field: Pattern Recognition, Image Processing, Biometric Feature Recognition,
Multi-modal Learning, Deep Hash Learning
艾伯塔大学博士
深圳市大数据研究院研究科学家及医疗大数据实验室主任
研究领域：整合分析、数据挖掘、大规模基因组数据分析、高性能计算、循证医学
Ph.D., University of Alberta
Experience: Research Scientist and Director of Medical Big Data Lab at Shenzhen Research
Institute of Big Data
Research Field: Meta-analysis, Data Mining, Large-scale Genomic Data Analysis,
High Performance Computing, Evidence-based Medicine
中国科学院博士
深圳市大数据研究院高级研究科学家（教授）、大数据基础理论与算法研究所所长，曾任英国伯明
翰大学数学学院讲师和副教授、中国科学院数学与系统科学研究院应用数学研究所运筹学研究室副
主任、中科院计算数学与科学工程计算、香港中文大学、多伦多大学博士后
研究领域：大系统优化理论与算法、稀疏信号处理的理论与算法、压缩感知算法、
线性逆问题与数值分析
Ph.D., Chinese Academy of Sciences
Experience: Professor of the Shenzhen Research Institute of Big Data (SRIBD), Director of the
Institute of Big Data Basic Theory and Algorithms, Former Lecturer and Associate Professor at
University of Birmingham, Former Deputy Director of Operations Research Office, Institute of Applied
Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Former
Postdocs at Computational Mathematics and Science Engineering Computing, Chinese Academy of
Sciences, The Chinese University of Hong Kong, and University of Toronto
Research Field: Applied Mathematics, Mathematical Optimization, Sparse Signal Reconstruction,
Compressed Sensing, Linear Inverse Problems and Numerical Analysis
赵云彬
ZHAO, Yunbin
教授 （客座）
Professor (Adjunct)
sds.cuhk.edu.cn 17
Faculty
数据科学与大数据技术专业于 2020 年开始招生。我们
现在身处一个数据的时代。在数据时代，企业和社会迫切需
要运用大数据技术分析、处理数据、提炼有效信息，并利用
数据做出更好的决策。如何利用安全、公平以及高效的算法
来创造价值已经成为各行各业关注的重要问题。在此背景下，
香港中文大学（深圳）数据科学学院开设数据科学与大数据
技术专业，为企业和社会的发展提供相应人才支持。
数据科学与大数据技术是一门跨学科专业，涵盖了从数据
收集、分析到决策的全部数据分析要素，涉及的领域包括运筹
学、统计学、机器学习、运营管理和决策科学等研究领域及相
关交叉领域。数据科学与大数据技术本科课程的目标，是培养
具备数据科学所需的扎实数学和统计基础、理解和规划数据分
析问题的计算和分析思维，以及对现实数据分析问题实现可扩
展性解决方案的实际操作能力的数据科学领域人才。
该专业的毕业生就业前景广泛，互联网的迅速发展，使
得大数据相关产业市场规模不断扩大，人才缺口也日益增大。
毕业生可在互联网、金融、医疗、制造、物流、教育等众多
行业就业，也可胜任知名企事业单位数据相关的工作，或前
往国际一流高校继续深造。
DATA SCIENCE AND
BIG DATA TECHNOLOGY
数据科学与大数据技术
本科专业
UNDERGRADUATE
PROGRAMMES
Data Science and Big Data Technology is an undergraduate
programme established by SDS of CUHK-Shenzhen, which
opens for application in 2020. We are now in the age of
data. In the era of data, enterprises and society urgently
need to use big data technology to analyze, process data,
extract effective information, and use data to make better
decisions. How to use safe, fair, and efficient algorithms to
create value has become an important issue in all walks of
life. In this context, SDS of The Chinese University of Hong
Kong, Shenzhen offers the major of Data Science and Big
Data Technology to provide corresponding talent support for
the development of enterprises and society.
Data Science and Big Data Technology is interdisciplinary in
nature and covers the complete pipeline of data analytics,
from data collection, to data analysis, and to decision
making. It covers research areas such as operations research,
statistics, machine learning, operations management and
decision science, and related cross-disciplines. We envision
the establishment of a rigorous undergraduate programme
that emphasizes the mathematical and statistical foundation
of data science, computational and analytical thinking for
understanding and formulating data analysis problems as
well as practical implementation to realize scalable solutions
to real-world data analytic problems.
Graduates of this programme have a wide range of
employment prospects, including the Internet, finance,
medical care, manufacturing, logistics, education and
many other industries. With the rapid development of the
Internet, the market of big data-related industries keeps
expanding and the talent gap is growing. Graduates can
also be qualified for the work related to data in well-known
enterprises and public institutions, or go to world-class
universities for further study.
18 School of Data Science
Discrete Mathematics
Visual Analytics
Numerical Methods
Bayesian Statistics
Advanced Machine Learning
Reinforcement Learning
Data Privacy and Ethics
Mathematical Introduction to
Deep Learning
Random Matrices and Their
Applications
Optimization II
Probability Theory
Statistical Inference
Statistical Computing
Introductory Econometrics
Game Theory and Business
Strategy
Quantitative Methods for
Policy Evaluation
Intermediate Econometrics
Investment Analysis and Portfolio
Management
Financial Data Analysis
Financial Computation
Multivariate Techniques with
Business Applications
Time Series
Statistical Modelling in Financial
Markets
Operations Management
Game Theory and Business Strategy
Networked Life
Topics in Supply Chain Management
Social Network Analysis and its
Business Application
Principles of Management
Supply Chain and Logistics
Current and Regional Issues
in Supply Chain and Logistics
Management
Big Data Marketing
Computational Biology
The Merge of Information Technology
and Biotechnology
Bioinformatics
Computational Genomics &
Proteomics
Design and Analysis of
Bioinformatics Algorithms
Genetic Engineering
Protein Structure Analysis and
Proteomics
Database System
C/C++ Programming
Computer Architecture
Operating System
Fundamentals of Speech and
Language Processing
Software Engineering
Parallel Programming
Design and Analysis of Algorithms
Computer Graphics
Mobile Computing with Internet
of Things
Cloud Computing
Social Networks
Practical High-Performance
Computing
Deep Learning and Applications
Data and Knowledge Management
Computational Imaging
更多申请信息请参见招生网：admissions.cuhk.edu.cn Please visit admission website for more info: intladmissions.cuhk.edu.cn
Undergraduate Programmes Data Science and Big Data Technology
sds.cuhk.edu.cn 19
专业选修 Major Elective Courses
学院课程 School Package
化学与生命科学
数据科学基础
Chemistry and Life Sciences
计算机实验 Computational Laboratory
计算机科学导论：
程序设计方法
Introduction to Computer Science:
Programming Methodology
Introduction to Data Science
线性代数与应用
力学
概率论基础
微积分（二）
微积分（一） Calculus I
Calculus II
Linear Algebra and Applications
Mechanics
Probability
数据结构
专业必修 Major Required Courses
Data Structure
机器学习 Machine Learning
随机模拟 Stochastic Simulation
数理统计
随机过程
最优化
Stochastic Processes
Optimization
Mathematical Statistics
博弈论与商业战略
政策评估的计量方法
中级计量经济学
投资分析与投资组合管理
金融数据分析
金融计算
多元技术及其商业应用
时间序列
金融市场的统计建模
营运管理
博弈论与商业战略
数据科学之应用：生活中的网络
供应链管理热点
社交网络分析及其商务应用
管理学原理
供应链与物流
供应链与物流管理现代和区域性问题
大数据营销
计算生物学
IT 和 BT 的融合及在生命与
健康科学中的应用
生物信息学
计算基因组学和蛋白质组学
生物信息算法设计及分析
基因工程学
蛋白质结构分析和蛋白质组学
数据库系统
C/C++ 程序设计
计算器体系结构
操作系统
语音与语言处理基础
软件工程
并行程序设计
算法设计及分析
计算器图形学
物联网移动计算
云计算
社交网络
应用高性能计算
深度学习与应用
数据与知识管理
计算摄影
离散数学
可视化分析
数值方法
贝叶斯统计
高等机器学习
强化学习
数据隐私和道德
深度学习中的数学
随机矩阵及其应用
最优化（二）
概率论
统计推断
统计计算
计量经济学导论
统计学是研究数据的收集、分析和诠释，从而获取
信息和支持决策的一门学科。统计学已广泛使用于各领
域，包括从生物学、社会科学、自然科学的研究到会计、
金融、医药、工程和政府决策的各种应用。
数据科学学院统计学专业旨在培养具有创新意识、
科学型和工程型相结合的高水平人才，帮助学生认识统
计学在各领域的广泛应用，拓宽学生的知识结构，培养
其解决各类实际问题的能力。本专业学生可以广泛接触
和学习商业、工程、自然科学和社会科学各领域中的问
题，让学生掌握统计学的基本理论，获得分析和解决实
际问题所需的方法技能。毕业生将能胜任工商业和政府
机构工作，以及有能力在科学、工程、工商管理等领域
进一步深造和从事研究。
Statistics is the discipline of the collection, analysis, and interpretation of
research data to obtain information and support decision-making. Statistics has
been widely used in various fields, from research in biology, social sciences,
and natural sciences to applications in accounting, finance, medicine,
engineering, and government decision-making.
Statistics programme in SDS aims to cultivate high-level talents who are
innovative, scientific and engineering, help students understand the wide
application of statistics in various fields, broaden their knowledge structure,
and cultivate their ability to solve various practical problems. Students of
this programme can be widely exposed to and learn problems in various
fields of business, engineering, natural science and social science, so that
students can master the basic theory of statistics and acquire the method
skills needed to analyze and solve practical problems. Graduates will be
qualified for jobs in industry, commerce and government agencies, as well
as the ability to pursue further studies and research in the fields of science,
engineering and business administration.
STATISTICS 统计学
2022 届毕业生就业数据 2022 Placement Data
的学生选择升学
82.53% of 2022 graduates decided 82.53% to pursue further study
根据 2023 年 QS/U.S.NEWS 世界大学排名，升学学生中 74.45% 将
攻读世界大学排名前 50 名高校的硕士 / 博士学位，如宾夕法尼亚大学、
耶鲁大学、杜克大学、哥伦比亚大学、密歇根大学、南洋理工大学、香
港科技大学、伦敦大学学院、悉尼大学等。
According to 2023 QS/US.NEWS World University Rankings, 74.45%
of them were admitted to top 50 universities, including University of
Pennsylvania, Yale University, Duke University, Columbia University,
University of Michigan, Nanyang Technological University, Hong Kong
University of Science and Technology, University College London, The
University of Sydney, etc.
就业单位不乏华为、腾讯、科大讯飞、兴业银行、
招商银行、中信银行、京东、欧莱雅、中广核智能
科技、深圳市公立学校等知名企业 / 事业单位。
12.65% of the graduates chose to work after
graduation. Mostly employed by well-known
companies and public institutions, including
Huawei, Tencent, iFLYTEK, Industrial Bank Co.,
Ltd., China Merchants Bank, China CITIC Bank, JD,
L’ORÉAL, CGN and Shenzhen Public Schools, etc.
12.65%
的同学选择创业
0.6% of the graduates chose 0.6% to start their own business
74.45% TOP50
20 School of Data Science
的同学选择就业
数值方法
实分析
高等线性代数
统计推断（二）
随机过程
广义线性模型
实验设计与分析
非参数统计
调查抽样
多元统计分析
时间序列
统计毕业设计
数据结构
贝叶斯统计
机器学习
常微分方程
金融及风险管理模拟方法
金融与风险之随机微积分
风险管理及衍生品的应用
金融市场的统计建模
数据库系统
离散数学
算法设计及分析
随机模拟
高等机器学习
深度学习与应用
强化学习
数据隐私和道德
深度学习中的数学
数据科学之应用：
生活中的网络
数字逻辑与系统
最优化（二）
概率论
生存数据模型
统计学专题（一）
统计学专题（二）
范畴性数据分析
计量经济学导论
财务管理
金融学基础
投资分析与投资组合管理
金融科技理论与实践
期权与期货
固定收益证券分析
C/C++ 程序设计
Numerical Methods
Real Analysis
Advanced Linear Algebra
Statistical Inference II
Stochastic Processes
Generalized Linear Models
Design and Analysis of Experiments
Nonparametric Statistics
Survey Sampling
Multivariate Statistical Analysis
Time Series
Statistical Capstone
Data Structures
Bayesian Statistics
Machine Learning
Ordinary Differential Equation
Simulation Methods for Risk
Management and Finance
Stochastic Calculus for
Finance and Risk
Risk Management with Derivatives
Statistical Modelling in
Financial Markets
Database System
Discrete Mathematics
Design and Analysis of Algorithms
Stochastic Simulation
Advanced Machine Learning
Deep Learning and Applications
Reinforcement Learning
Data Privacy and Ethnics
Mathematical Introduction to
Deep Learning
Networked Life
Digital Logic and Systems
Optimization II
Probability Theory
Survival Modelling
Selected Topics in Statistics I
Selected Topics in Statistics II
Categorical Data Analysis
Introductory Econometrics
Financial Management
Foundation of Finance
Investment Analysis and Portfolio
Management
Fintech Theory and Practice
Options and Futures
Fixed Income Securities Analysis
C/C++ Programming
Undergraduate Programmes
Statistics
专业选修 Major Elective Courses
sds.cuhk.edu.cn 21
数学分析
专业必修 Major Required Courses
Mathematical Analysis
数理统计
最优化 Optimization
Mathematical Statistics
线性模型
统计推断
统计计算
Linear Models
Statistical Computing
Statistical Inference
学院课程 School Package
化学与生命科学
数据科学基础
Chemistry and Life Sciences
计算机实验 Computational Laboratory
计算机科学导论：
程序设计方法
Introduction to Computer Science:
Programming Methodology
Introduction to Data Science
线性代数与应用
力学
概率论基础
微积分（二）
微积分（一） Calculus I
Calculus II
Linear Algebra and Applications
Mechanics
Probability
计算机科学与技术是信息化的核心，也是现代社会规模最
大的学科专业之一，具有学科涵盖面广、应用面宽、应用层次
跨度大的特点。在信息时代，各行业对计算机人才的需求日益
突出，特别是对前沿学科的计算机人才的需求显著增长。
数据科学学院计算机科学与技术专业紧密贴合国家和粤港
澳大湾区信息技术发展的迫切需求，目标在计算机核心基础、
计算机网络、软件工程、信息与网络安全、人工智能、机器学习、
模式识别、自然语言处理、语音与视觉等学科方向建设一个国
际一流的学科，培养具有创新意识、科学型和工程型相结合的
高水平计算机科学与技术人才。为了实现这一目标，我们在全
球招聘了一流专家与学者，精编学科课程，并配置先进的教学
科研设施。本专业的毕业生将会在数学等基础学科上建立扎实
的基础，并广泛了解、应用交叉学科的知识，同时掌握计算机
专业的知识和技能，获得较强的计算机系统的分析、设计、编
程和应用能力。其中，机器学习、人工智能和数据科学将是重
点应用方向。毕业生将能胜任在社会各个领域内从事计算机方
面的前沿工作，以及在学术领域进一步的深造学习中出类拔萃。
COMPUTER SCIENCE
AND ENGINEERING
计算机科学与技术
2022 届毕业生就业数据
Placement Data
64.42%
选择就业的学生占比为 30.77%，平均年薪高达 24.25 万，毕业生就职
于华为、腾讯、阿里巴巴、微软、哔哩哔哩、中兴通讯、小马智行、中
国农业银行、德勤会计师事务所、深圳市公立学校等知名企业 / 事业单位。
30.77% of the graduates chose to work after graduation. The average
annual salary is 242,500 RMB. Mostly employed by well-known
companies and public institutions, including Huawei, Tencent, Alibaba
Group, Microsoft, bilibili, Zhongxing Telecom Equipment, Pony.ai,
Agricultural Bank of China, Deloitte, and Shenzhen Public Schools, etc.
30.77%
64.42% 的同学选择在知名高校继续深造，包括康奈尔大学、芝加哥
大学、新加坡国立大学、约翰霍普金斯大学、纽约大学、加州大学圣
地亚哥分校、多伦多大学、哥本哈根大学、香港中文大学等。
64.42% of students decided to pursue further study in well-known
universities around the world, including Cornell University, University
of Chicago, National University of Singapore, Johns Hopkins
University, New York University, University of California, San Diego,
University of Toronto, University of Copenhagen, and The Chinese
University of Hong Kong, etc.
Computer Science and Engineering is the core of
information technology, and also one of the largest
disciplines in modern society. It has the characteristics of
wide discipline coverage, wide application and large span
of application levels. In the information age, the demand
for computer talents in various industries is increasingly
prominent, especially the demand for computer talents in
frontier disciplines has increased significantly.
The programme of Computer Science and Engineering
in SDS closely meets the urgent needs of information
technology development of the country and the
Guangdong-Hong Kong-Macao Greater Bay Area.
CUHK-Shenzhen is committed to carrying out cuttingedge research in the fields of Computer Science and
Engineering. To achieve this goal, faculties and scholars
of high-caliber have been globally recruited; curriculum
has been meticulously designed with advanced teaching
and research facility. In this programme, machine
learning, artificial intelligence and data science will be
the key application directions. Students will acquire a
solid foundation in mathematics and broad knowledge in
interdisciplinary applications. They will also master the
knowledge and skills of computer science which enable
them to obtain strong analysis, design, programming
and application capabilities of computer systems.
Graduates will be capable to excel in computer science
in various fields of society, and in pursuing research and
development in academia.
22 School of Data Science
24.25w
的学生选择升学
64.42% of 2022 graduates decided
to pursue further study
专业选修 Major Elective Courses
Undergraduate Programmes Computer Science and Engineering
sds.cuhk.edu.cn 23
生物信息学
Java 程序设计导论
程序设计语言原理
语音与语言处理基础
人工智能之基本原理
多媒体系统导论
并行程序设计
数据挖掘技术
自然语言处理
人机接口导论
计算机图形学
物联网移动计算
云端计算
编译器设计
互联网编程与应用
可视化分析
数值方法
随机模拟
高等机器学习
深度学习与应用
强化学习
数据隐私和道德
计算成像
数据科学之应用：生活中的网络
机械人学概论
电子游戏设计与开发
机械人与智能系统
计算机网络
机器人操作系统与编程
中级微观经济理论
计量经济学导论
博弈论与商业战略
微处理与计算机系统
网络 : 技术、经济和社会
编码及密码学导论
数字图像处理
创业原则
金融数据分析导论
最优化
最优化（二）
物理实验
统计计算
随机过程
Bioinformatics
Introduction to Java Programming
Principles of Programming
Languages
Fundamentals of Speech and
Language Processing
Fundamentals of Artificial
Intelligence
Introduction to Multimedia
Systems
Parallel Programming
Techniques for Data Mining
Natural Language Processing
Introduction to Human-Computer
Interaction
Computer Graphics
Mobile Computing with Internet
of Things
Cloud Computing
Compiler Construction
Internet Programming and
Applications
Visual Analytics
Numerical Methods
Stochastic Simulation
Advanced Machine Learning
Deep Learning and Applications
Reinforcement Learning
Data Privacy and Ethnics
Computational Imaging
Networked Life
Introduction to Robotics
Video Games Design and
Development
Robotics and Intelligent Systems
Computer Networks
Programming for Robotics
Intermediate Microeconomic
Theory
Introductory Econometrics
Game Theory and Business
Strategy
Microprocessors and
Computer Systems
Networks: Technology,
Economics and Society
Introduction to Coding and
Cryptography
Digital Image Processing
Principles of Entrepreneurship
Introduction to Financial
Data Analysis
Optimization
Optimization II
Physics Laboratory
Statistical Computing
Stochastic Processes
学院课程 School Package
化学与生命科学 Chemistry and Life Sciences
计算机科学导论：
程序设计方法
Introduction to Computer Science:
Programming Methodology
计算机科学与 Java
程序设计导论
Introduction to Computer
Science and Java Programming
微积分（二）
力学
微积分（一）
数据科学基础 Introduction to Data Science
概率论基础 Probability
Calculus I
Calculus II
计算机实验 Computational Laboratory 线性代数与应用 Linear Algebra and Applications
Java 程序设计实验 Computational Laboratory Using Java
概率及统计（一） Probability and Statistics I
Mechanics
专业必修 Major Required Courses
离散数学 Discrete Mathematics 数据库系统 Database System
机器学习
软件工程 Software Engineering
Machine Learning
C/C++ 程序设计 C/C++ Programming
计算机体系结构 Computer Architecture
操作系统
数据结构 Data Structures
Operating System 数字逻辑与系统
算法设计及分析 Design and Analysis of Algorithms
Digital Logic and Systems
金融工程专业由数据科学学院与经管学院、理工学院与联
合开设。本课程的毕业生具有较强的计量及分析能力，有成为
未来金融行业领袖的潜质，并能满足金融行业对人才的需求。
毕业生将具备全面的金融建模与预测能力，因此能胜任对计量
及分析能力要求极高的职位与工作，例如估值、投资组合分析、
资产配置、信用分析、风险模型，以及结构性融资。本课程为
毕业生在投资银行、商业与企业银行，以及金融服务单位中的
职业发展打下良好基础。
Financial Engineering is jointly launched by the School of Data
Science (SDS), the School of Management and Economics (SME),
the School of Science and Engineering (SSE). The programme is
set up to meet the finance industry’s demand for graduates with
strong quantitative and analytical skills who have the potential to
become leaders in the finance industry. Graduates are equipped
with sound financial modeling and forecasting skills, and are
ideally suited to positions and tasks that require strong quantitative
and analytical skills such as valuation, portfolio analysis, asset
allocation, credit analysis, risk modeling, and structured finance.
The programme also provides a good foundation for careers in
investment banking, commercial and corporate banking and
financial services.
24 School of Data Science
学院课程 School Package
财务会计导论
微观经济学基础
财务管理
计算机科学导论：程序设计方法
金融基础
计算机实验
微积分（一）
线性代数
Introductory Financial Accounting
Basic Microeconomics
Financial Management
Introduction to Computer Science: Programming Methodology
Foundation of Finance
Computational Laboratory
Calculus I
Linear Algebra
微积分（二） Calculus II
概率及统计（一） Probability and Statistics I
FINANCIAL ENGINEERING
金融工程 （三院合办 Joint Programme with SME and SSE）
本课程提供以下两个专修方向：
量化金融 金融科技
This programme provides two streams:
Quantitative Finance FinTech
中国法律环境、商业道德与
企业社会责任
Java 程序设计导论
离散数学
C/C++ 程序設計
数据结构
操作系统
数据库系统
人工智能之基本原理
数据挖掘技术
机器学习
高等机器学习
应用概率和随机过程
博弈论与商业战略
计算机与网络安全
网络分析与智能
中国与世界的金融市场
行为金融学
期权与期货
固定收益证券分析
公司金融
资产定价
金融数据分析
金融计算
sds.cuhk.edu.cn 25
专业必修 Major Required Courses
Legal Environment, Business Ethics
and CSR in China
Introduction to Java Programming
Discrete Mathematics
C/C++ Programming
Data Structures
Operating System
Database System
Fundamentals of Artificial Intelligence
Techniques for Data Mining
Machine Learning
Advanced Machine Learning
Applied Probability and Stochastic
Process in Business
Game Theory
Computer and Network Security
Web Analytics and Intelligence
Financial Markets in China and
the World
Behavioral Finance
Options and Futures
Fixed Income Securities Analysis
Corporate Finance
Asset Pricing
Financial Data Analysis
Financial Computation
FinTech Regulation and Legal Policy
Blockchain and Decentralized Applications
Internship
Probability Theory
Stochastics Differential Equations
Big Data Marketing
Risk Management with Derivatives
Regression Analysis
Stochastic Process
Time Series
专业选修 Major Elective Courses
计量经济学导论
量化金融 Quantitative Finance Stream
Introductory Econometrics
投资分析与投资组合管理 Investment Analysis and Portfolio Management
离散数学
数据结构
计量经济学导论
金融科技理论与实践
投资分析与投资组合管理
机器学习
最优化
概率及统计（二）
Discrete Mathematics
Data Structures
Introductory Econometrics
Fintech Theory and Practice
Investment Analysis and Portfolio Management
Machine Learning
Optimization
Probability and Statistics II
金融科技 FinTech Stream
Undergraduate Programmes Financial Engineering
金融科技规则与法律
区块链与去中心化应用
金融工程实习
概率论
随机微分方程
大数据营销
风险管理及衍生品的应用
回归分析
随机过程
时间序列
期权与期货
常微分方程
固定收益证券分析
最优化
数学建模
概率及统计（二）
Options and Futures
Ordinary Differential Equations
Fixed Income Securities Analysis Computational Finance
Optimization
Mathematical Modeling
Probability and Statistics II
金融科技理论与实践 Fintech Theory and Practice
数据科学理学硕士项目由香港中文大学（深圳）数据科学
学院和经管学院共同开设，并与深圳市大数据研究院和深圳高
等金融研究院合作。项目旨在使学生掌握大数据及商业分析方
面的基础理论知识和专业技能，接触到支撑大数据技术的前沿
理论与方法，并能在商业、政府、安全、医疗、生物、自然科
学、环境等领域中充分利用所学知识解决与大数据采集、管理
及分析相关的问题。课程采用全英文教学，学制 24 个月。学
生也可以在就读期间参与到业界实习、实验室科研、海外交换，
亦或修读更多课程，从而将学制延长至最多 36 个月。两所学
院及研究院的优秀师资将共同担任项目授课教师。
M.Sc. in Data Science is a joint programme launched by the
School of Data Science (SDS) and the School of Management
and Economics (SME), in collaboration with Shenzhen
Research Institute of Big Data (SRIBD) and Shenzhen Finance
Institute (SFI). The programme is aimed to equip students
with fundamental knowledge as well as skills in big data and
business analytics, and provide students with the cuttingedge theories and methods of big data technology, so that our
graduates will be able to tackle issues of data capture, storage
and analysis in various sectors, including business, government,
security, healthcare, biology, science and environment. All
courses are taught in English. Programme duration is 24
months. Alternatively, students may participate in a wide range
of industrial internships, research work, worldwide exchange
programmes, studying more courses and extend their studies
to 36 months. Faculty members from two schools and research
institutes will serve as instructors together.
课程设置及要求 COURSE REQUIREMENTS
数据科学理学硕士项目的学生需在学习期限内完成 3 门必修课和 11 门选修课，每门课程 3 个学分；或 3 门必修课和 9 门选
修课，并在学术和 / 业界导师的指导下，完成 6 个学分的毕业项目。学生毕业时需完成共计 42 个学分。
Students need to complete 3 required courses and 11 elective courses offered in the regular terms within the normative study period, or
3 required courses and 9 elective courses with completing a Capstone Project supervised by academic faculty or industrial supervisors.
Each course carries 3 credits. The Capstone Project carries 6 credits. Students should complete total 42 credits in order to graduate.
26 School of Data Science
TAUGHT POSTGRADUATE
PROGRAMMES 硕士项目
MASTER OF SCIENCE
IN DATA SCIENCE
数据科学理学硕士
以上数据表明，数据科学理学硕士项
目毕业生在充满竞争的就业市场中都
表现出了很强的竞争力与吸引力。
As the graduates of MSc in Data
Science Programme, the figures
demonstrate that each graduate gains
strong employment traction despite of
the challenges in the job market.
2022 届毕业生就业数据 2022 Employment Data
深造读博
Further study
6%
就业率
Employment rate
96%
平均年薪（RMB）
Average salary (RMB)
343,000
任职于金融领域
Students in finance sectors
23%
任职于其他机构
Students in other sectors
17%
任职于科技型企业
Students in technology
companies
60%
香港中文大学（深圳）将为优秀的申请人提供各类奖学金支持。
CUHK-Shenzhen may offer various kinds of scholarships to
selected applicants.
网申报名 Online Application:
https://pgapply.cuhk.edu.cn/
项目官网 ：http://mscds.cuhk.edu.cn/
Official website: http://mscds.cuhk.edu.cn/en/
sds.cuhk.edu.cn 27
Taught Postgraduate Programmes Master of Science in Data Science
* 注：以上列表未包含其他硕士 / 博士项目共享课程。课程安排以最终开课为准。
Note: The above course list excludes the courses that are offered by other master / Ph.D. programmes. The courses offered are subject to change.
必修课（共计 3 门 /9 个学分） Required Courses (3 courses/9 units)
选修课（选修 11 门 /33 个学分或 9 门 + 毕业项目 /6 个学分）
Elective Courses (Select 11 courses/33 units or 9 courses + Capstone Project/6 units)
Theory of Statistics
Python Programming
Advanced Time Series Analysis
Artificial Intelligence in Medical Imaging
Natural Language Processing
Image Processing and Computer Vision
Applied Regression Analysis
Analysis of Numerical Algorithms
Artificial Intelligence
Applied Parallel Programming
Big Data Modeling and Management
Web Analytics
Data Visualization
Blockchain
Cloud Computing
Fintech Theory and Practice
Dynamic Programming
Stochastic Process
Deep Learning and Their Applications
Reinforcement Learning
统计学理论
Python 编程
高级时间序列分析
医学影像与人工智能
自然语言处理
图像处理与计算机视觉
应用回归分析
数值算法分析
人工智能
应用并行编程
大数据建模与管理
网络分析
数据可视化
区块链
云计算
金融科技理论与实践
动态规划
随机过程
深度学习及其应用
强化学习
入学要求及注意事项
授课型研究生课程申请资格
1. 毕业于认可的大学，获得学士学位，荣誉等级不低于二等；或
2. 毕业于认可的大学，获得学士学位，成绩不低于“B”；或
3. 等同大学本科的资历。
申请者 * 必须符合英语要求（符合以下要求之一）：
1. 在香港地区的大学取得学位 a 或修读并完成以英语为教学语
言的学位课程 ;
2. 在下列任一英语语言考试中取得如下要求的成绩 b:
托福 : 550( 笔试 )/79( 机考 );
雅思 ( 学术 ): 6.5;
GMAT: Band 21 (Verbal);
3. 在下列任何一门考试中取得英语及格成绩 :
Hong Kong Advanced Level Examination (AS Level);
Hong Kong Higher Level Examination;
CUHK Matriculation Examination;
General Certificate of Education Examination (GCE)
Advanced Level (A-Level)/Advanced Subsidiary
Level (AS-Level);
4. 在香港中学文凭考试 Hong Kong Diploma of Secondary
Education (HKDSE) Examination 英语学科取得第四级或以上
成绩 ;
5. 取得公认的专业资格，并证明该专业资格考试使用英语进行
测试。
备注 :
a. 基于默认香港地区的学位课程均以英语授课。请注意香港中文大
学（深圳）研究生院仍可要求申请人提供其他相关证明文件，以证明
其英语水平符合要求。
b. 托福和雅思成绩自考试之日起两年有效。 GMAT 成绩自考试之日
起 5 年内有效。
* 部分以中文授课的课程除外，各研究生课程可能会有特殊的入学申请要求，
请联系各自课程招生老师了解详情。
Entry Requirements
For a Master's Programme, the applicant shall have:
1. Graduated from a recognized university and obtained a Bachelor's degree,
normally with honours not lower than Second Class; or
2. Graduated from an honours programme of a recognized university with a
Bachelor's degree, normally achieving an average grade of not lower than \"B\" ; or
3. Completed a course of study in a tertiary educational institution and obtained
professional or similar qualifications equivalent to an honours degree.
To fulfill the University’s minimum English language requirements for
admission to postgraduate programmes, applicants should have:
a. obtained a degree from a university in Hong Kong or taken a degree
programme of which the medium of instruction was English; or
b. achieved scores in the following English Language tests as indicated:
i. TOEFL: 550 (Paper-based)/79 (Internet-based);
ii. IELTS (Academic): 6.5;
iii. GMAT: Band 21 (Verbal); or
c. obtained a pass grade in English in one of the following examinations:
i. Hong Kong Advanced Level Examination (AS Level);
ii. Hong Kong Higher Level Examination;
iii. CUHK Matriculation Examination;
iv. General Certificate of Education Examination (GCE) Advanced Level (A-Level)/
Advanced Subsidiary Level (AS-Level); or
d. achieved Level 4 or above in the English Language subject of the Hong Kong
Diploma of Secondary Education (HKDSE) Examination; or
e. obtained a recognized professional qualification, provided that the examination
was conducted in English.
Notes:
1. This is based on the understanding that English is the medium of instruction of degree
programmes offered by universities in Hong Kong. Moreover, graduates from universities in
Hong Kong should have fulfilled the English language requirements of the institution concerned
when they were admitted to the degree programmes. The CUHKSZ Graduate School may
request applicants to provide additional supporting documents to prove their English proficiency.
2. TOEFL and IELTS scores are considered valid for two years from the test date. GMAT scores
are considered valid for five years from the test date.
1
2
机器学习 Machine Learning
数据挖掘 Data Mining
优化理论与建模 Optimization and Modeling
毕业项目（6 学分） Capstone Project (6 units)
香港中文大学（深圳）金融工程硕士项目创
立于 2015 年，是数据科学学院与香港中文大学
沙田校区工程学院合办的全日制授课型学位课程
项目。该项目旨在通过深入而坚实的金融工程理
论和实践的训练，帮助立志投身于证券、银行、
基金、金融风险管理、策略咨询、量化投资等行
业的学生掌握相关金融知识，定量分析方法以及
程序设计技术，使之具备应对迅速发展的中国以
及国际金融市场所带来的挑战的能力。近年来，
项目在传统金融工程课程基础上，又开设了机器
学习、数据科学、量化投资、区块链应用等新课
程，以增强毕业生综合竞争力。
除“中国金融市场概论”外，项目为全英文
授课。学制两年，包括秋季、 春季以及夏季（短）
三个学期。学生要求通过 5 门必修课和至少 5
门选修课的学习达到毕业要求（至少 30 学分）。
项目不断推进与企业合作，同时鼓励学生积极参
与实习和科研，使其在校期间就有机会发挥所学，
服务企业与社会。在国际化方面，项目已经与
Bocconi University 金融硕士项目建立了学生
交换机制，同时我们亦与 Questrom Business
School of Boston University 的数理金融与金
融科技硕士项目一起推出合作学位课程。
28 School of Data Science
MASTER OF SCIENCE IN
FINANCIAL ENGINEERING
金融工程理学硕士
The Chinese University of Hong
Kong, Shenzhen launched the Master
of Science program in Financial
Engineering (M.Sc. in FE) in 2015.
Currently the full-time taught program is
jointly organized by the School of Data
Science and the Faculty of Engineering
at the Shatin Campus of The Chinese
University of Hong Kong. Through indepth and solid training in financial
engineering theory and practice, the
program aims to equip our students
with hands-on financial knowledge,
quantitative analytical methods and
programming skills, so they can
face the challenge from the rapidly
changing Chinese and international
financial markets. In the end, these
can help them enter industries such
as securities, banking, fund, financial
risk management, strategic consulting
and quantitative investment. In recent
years, the program leverages on the
quantitative finance fields to start new
courses in Machine Learning, Data
Science, Quantitative Investment and
Blockchain Applications, to strengthen
the competitiveness of our graduates.
Apart from the “Introduction to Chinese
Financial Markets” course, all courses
are taught in English. The normal study
period is two years, including the Fall,
Spring and Summer (short) terms.
To fulfill the graduation requirements
(at least 30 credits), students need to
complete 5 required courses and at
least 5 elective courses. The program
strives to increase the collaboration with
the industry. We encourage the students
to take part in internship and research,
so they can have the opportunities
to apply what they learn to service
the corporates and the society. In an
international perspective, the program
has established an exchange program
with the Master of Finance program
at Bocconi University; meanwhile,
we have introduced the Collaborated
Degree Program with the M.Sc. in
Mathematical Finance and Financial
Technology program of Questrom
Business School of Boston University.
金融工程理学硕士项目 M.Sc. in Financial Engineering (MFE)
全日制 Full-time
理学硕士 Master of Science
30 学分 30 credits
学位 Degree
学制 Mode of Study
学期 Study Period 2 年（3 个学期 / 年） Two years (3 terms per year)
学费 Tuition Fee 26.8 万人民币 RMB268,000
奖学金 Scholarships
学分要求 Credit Unit
Requirements for Graduation
优先录取奖学金
（最高可达全额学费）
新生奖学金
学习优异奖学金
Early Admission Scholarship
(up to full tuition amount)
Entrance Scholarship
Academic Excellence
Scholarship
Virtue Prize
Overseas Study Scholarship
Financial Aid (need based)
约礼奖
海外交换学习奖学金
助学金
（根据财务状况）
sds.cuhk.edu.cn 29
金融数据分析
定量风险管理
利率期限模型和固定收益证券
外汇与大宗商品市场建模
信用风险模型和产品
金融工程中的计算方法
演算法交易
金融工程专题 - 公司金融及
风险管理
金融工程专题 - 金融与经济学
中的数据分析与统计建模 ( 一 )
金融工程专题 - 金融与经济学
的数据分析与统计建模 ( 二 )
Financial Data Analysis
Quantitative Risk Management
Term Structure Models and
Fixed-income Securities
Foreign Exchange and
Commodity Market Modeling
Credit risk Modeling
and Products
Computational Methods in
Financial Engineering
Algorithm Trading
Special Topics in Financial
Engineering
– Corporate Finance and
Risk Management
Special Topics in Financial
Engineering – Data Analytics
and Statistical Modeling in
Finance and Economics I
Special Topics in Financial
Engineering – Data Analytics
and Statistical Modeling in
Finance and Economics II
Project
Data Sciences in Financial
Engineering
Internship Training 1
Internship Training 2
Quantitative Investment
Venture Capital &
Entrepreneurial Finance
Machine Learning and Its
Applications
Financial Engineering
Practicum
Regulatory Technology
Artificial Intelligence in
Financial Engineering
Blockchains with
Applications
Programming for Financial
Engineering
选修课 Elective Courses
金融工程硕士项目将为优秀的申请人提供各类奖学金支持。
The Master of Financial Engineering program will support outstanding
applicants with scholarships.
网申报名 Online Application:
https://pgapply.cuhk.edu.cn/
金融工程研究
数据科学在金融工程中的应用
校外实习 ( 一 )
校外实习 ( 二 )
数量化投资
风险投资与企业金融
机器学习以及其应用
金融工程研习
监管科技
人工智能在金融工程中的应用
区块链与应用
程式设计在金融工程中的应用
请申请者通过网申提交以下各项材料：
1. 学历证明
（毕业证和学位证或在读证明）
2. 官方成绩单
3. 英语水平证明
（雅思、或托福、或 GMAT）
4. 个人简历
Applicants are required to submitted the required application
materials as below:
所有申请者须满足我校研究生录取条件
http://gs.cuhk.edu.cn/page/26
申请信息
5. 个人陈述
6. 身份证扫描件
7. 两位推荐人信息
（至少 1 位为学术导师）
8. 职业证书（如适用），
及其他相关证明材料
Application Information
All applicants should fulfill the requirements:
http://gs.cuhk.edu.cn/page/26
1. A copy of Bachelor's and/or
Master's Degree Certificate or
Student Status Certificate
2. A copy of transcript
3. A copy of TOEFL/IELTS/GMAT
score sheet
4. Curriculum Vitae
5. Personal Statement
6. A copy of ID card
7. Contact details of two referees
(At least one is an academic tutor)
8. A copy of Professional Certificates
(if applicable), and other supporting
documents
更多招生信息请登录 More Information:
https://mscfe.cuhk.edu.cn/
Taught Postgraduate Programmes Master of Science in Financial Engineering
* 备注：以上公司 / 学校排名不分先后顺序。
* This list of company/school is in no particular order.
课程设置 COURSE REQUIREMENTS
必修课 Required Courses
最优化理论 Optimization
随机模型
投资科学
Stochastic Models
Investment Sciences
中国金融市场概论 Introduction to Chinese Financial Markets
金融衍生品 Financial Derivatives
同学就业城市主要分布在北上广深等一线城市，拿到
了众多行业知名公司及知名学府的录取，例如中金公
司、中信证券、华泰证券、广发证券、申万宏源证券、
国泰君安证券、国信证券、银华基金、创金合信基金、
鸣石投资、灵均投资、阿里巴巴、字节跳动、腾讯、百度、
中国农业银行、中国建设银行、平安银行、交通银行等；
升学院校如香港中文大学、东南大学、波士顿大学。
The work locations for 2022 graduates are Beijing,
Shanghai, Guangzhou and Shenzhen. They received offers
from top companies and universities, such as CICC, CITIC
Securities, Huatai Securities, GF Securities, Shenwan
Hongyuan Securities, Guotai Junan Securities, Guosen
Securities, Yinhua Fund, Truvalue ASSET MANAGEMENT,
Mingshi Investment, LinJun Investment, Alibaba Group,
ByteDance, Tencent, Baidu, AGRICULTURAL BANK OF
CHINA, China Construction Bank, Ping An Bank, Bank
of Communications, etc.; Institutions of higher learning
include The Chinese University of Hong Kong, Southeast
University, Boston University.
选择直接就业
Chose to work
93.75%
选择继续深造
Further studies
3.75%
年薪中位值（RMB）
Median salary (RMB)
年薪最高值（RMB）
Maximum salary (RMB)
2022 届毕业生就业数据 2022 Placement Data
33.25w
平均年薪 (RMB)
Average salary (RMB)
97.5%
项目就业率
Placement rate
* 注：统计数据截止至 2023 年 3 月 Note: As of March 2023
30w 64.92w
30 School of Data Science
生物信息学硕士专业是一项跨领域的学科，由香港中文大学（深
圳）医学院和数据科学学院共同开设，涵括生命科学、计算科学与
数据科学、物理、化学、统计等基础学科知识。近年来，生物信息
学已成为现代生物医学研究不可或缺的关键支点，从生物大数据中
挖掘新颖的生物标志物与分子调控机制，进而研制出疾病诊断与治
疗的方案，在生物技术及生物制药行业中的权重日益增长。在国家
与企业的大力支持下，粤港澳大湾区的生物医药产业正快速增长，
其中新药开发、检测试剂研发、医学临床应用更是知识密集产业。
本项目将进一步借助香港中文大学（深圳）医学学科群、生命科学、
数据科学等方面发展优势，培养市场紧缺的且具有生命科学与新药
开发专业知识的跨学科人才。
MASTER OF SCIENCE
IN BIOINFORMATICS
生物信息学理学硕士
The master programme in Bioinformatics is a joint programme
launched by School of Medicine and School of Data Science.
This programme serves as a solid foundation in cross-disciplinary
learning, creative thinking, practical problem-solving skills, and
a keen sense of bioinformatics for the emerging biotechnologies
and their future developments. With the well-designed study
scheme of this program, students are expected to be welleducated to achieve the forefront of leadership in the fields of
bioinformatics and biomedical sciences.
Bioinformatics is a cross-disciplinary discipline, including life
sciences, physics, chemistry, statistics, computer science,
and data science. Bioinformatics and computational biology
have become the cornerstone of modern biology. It can explore
the life processes of biological systems, mine novel biological
mechanisms from biological big data, and ultimately develop
disease diagnosis and treatment options. Recent advancements
in this area are reshaping every aspect of biological sciences,
agricultural sciences, medical research, health care systems, and
biological industries. The biological industries, especially drug
development sectors, are also fast-growing in China, especially in
the Pearl River Delta. There is thus a rapidly growing demand
for talented professionals with specialized knowledge, skills, and
abilities in bioinformatics and computational biology.
课程设置 CURRICULUM
在学习周期中修满 36 学分，其中必修课 15 学分和选修课 21 学分。另根据学校要求，对于 2021-22 学年及之后入学的研究生
（不含国际生），国情教育课程为必修科目。
Total 36 units in study period, including 15 units for required courses and 21 units for elective courses. In addition, all graduate
students (applicable to all students with Chinese nationality) admitted in CUHK, Shenzhen in 2021-22 and thereafter are required to
complete the Civic Education (CE) courses.
专业选修课 Elective Courses
Topics in Computer-Aided Drug Design
Selected Topics in Bioinformatics Algorithms
Computational Structural Biology
Computational Proteomics and
Functional Prediction
Biological Databases Design and
Data Visualization
计算机辅助药物设计
专题研讨
生物信息算法特论
计算结构生物学
计算蛋白质组学与功能预测
生物数据库设计与数据
可视化
深度学习
分子药理学及现代
药物研发
专题研究
深度学习特论
物理分子生物学
Deep Learning
Molecular Pharmacology and
Modern Drug Design
Research Project
Selected Topics in Deep Learning
Physical Basis of Molecular Biology
专业必修课 Required Courses
生物信息学的理论和算法 Theories and Algorithms in
Bioinformatics
计算分子建模与设计 Computational Molecular
Modeling and Design
生物医学研究中的机器学习 Machine Learning for
Biomedical Research
生物医学研究中的统计方法 Statistical Methods for
Biomedical Research
国情教育课程 Civic Education Courses
基因组信息学 Genome Informatics
sds.cuhk.edu.cn 31
1. 毕业于认可的大学，获得学士学位。成绩不低于 80/100，
平均绩点不低于 3.0/4.0；
2. 须符合英语要求（符合以下要求之一）：
1) 在香港地区的大学取得学位 (a) 或修读并完成以英语为教学
语言的学位课程；
2) 在下列任一英语语言考试中取得如下要求的成绩 (b) ：
- 托福 : 550( 笔试 )/79( 机考 );
- 雅思 ( 学术 ): 6.5;
- GMAT: Band 21 (Verbal);
3) 在下列任何一门考试中取得英语及格成绩 :
- Hong Kong Advanced Level Examination (AS Level);
- Hong Kong Higher Level Examination;
- CUHK Matriculation Examination;
- General Certificate of Education Examination (GCE)
Advanced Level (A-Level)/Advanced Subsidiary Level
(AS-Level);
4) 在香港中学文凭考试 Hong Kong Diploma of Secondary
Education (HKDSE) Examination 英语学科取得第四级或以上成绩 ;
5) 取得公认的专业资格，并证明该专业资格考试使用英语进行测试。
* 备注 :
a. 基于默认香港地区的学位课程均以英语授课。请注意香港中文大学
（深圳）研究生院仍可要求申请人提供其他相关证明文件，以证明其
英语水平符合要求 ;
b. 托福和雅思成绩自考试之日起两年有效；GMAT 成绩自考试之日起 5
年内有效。
1. Graduated from an honours
programme of recognized
university with a Bachelor's degree,
normally achieving an average
grade of GPA≥3.0/4.0, or 80/100, or
equivalent;
2. Fulfilled the 'English Language
Proficiency Requirement':
The applicant should either:
1) have a degree from university in Hong
Kong (a), or recognized university with
English as teaching language;
2) submit one of the following original
score reports/certificates for assessment
by the Programme concerned (b):
- TOEFL (Not lower than 550 paperbased; 213 computer-based; and 79
internet-based);
- IELTS (Academic, not lower than
Band 6.5).
- GMAT (Verbal, not lower than 21);
3) possess a pass grade in English in
one of the following examinations:
- Hong Kong Advanced Level
Examination (AS Level);
- Hong Kong Higher Level Examination;
- CUHK Matriculation Examination;
- General Certificate of Education
Examination (GCE) Advanced Level
(A-Level)/Advanced Subsidiary Level
(AS-Level);
4) achieve Level 4 or above in the
English Language subject of the
Hong Kong Diploma of Secondary
Education (HKDSE) Examination;
5) Obtain a recognized professional
qualification and prove that the
professional qualification exam is
conducted in English.
* Note:
a. Based on the condition that Hong Kong
degree programs are all taught in English.
Please note that the Graduate School of The
Chinese University of Hong Kong, Shenzhen
may still require applicants to provide other
relevant supporting documents to prove
that their English proficiency meets the
requirements;
b. TOEFL and IELTS scores are valid for two
years from the date of the test; GMAT scores
are valid for 5 years from the date of the test.
申请要求 Application Requirements
申请材料 Application Materials
网申报名 Online Application:
https://pgapply.cuhk.edu.cn/
申请信息 Application Information
2022 年 9 月 1 日 - 2023 年 7 月 15 日（截止日期之前均可提交申请）
September 1, 2022 - July 15, 2023 (Please submit before the deadline.)
申请时间 Application Time
A copy of Bachelor's and/or Master's Degree Certificate or Student Status Certificate
A copy of transcript (Chinese or English stamped with the official seal of
the undergraduate institution)
A copy of TOEFL/IELTS/GMAT score sheet
Curriculum Vitae (English)
Personal Statement (English)
A copy of ID card (Front & Back)
Contact details of two referees
Other supporting documents
学历证明（毕业证和学位证或在读证明）
官方成绩单（中文或英文，盖有本科院校公章）
英语水平证明（雅思、托福或 GMAT）
个人简历（英文）
个人陈述（英文）
身份证扫描件（正反面）
两位推荐人信息及其推荐信
其他相关证明材料
学习模式 Duration of Studies
学习费用 Fees
学习语言 Language 英语 English
香港中文大学理学硕士学位 Master of Science degree from The Chinese University of Hong Kong
总学费 175,000 人民币，依据学习周期支付。RMB 175,000 for the whole programme, paid annually based on mode of study.
学位授予 Degree Awarded
1.5 年，最长不超过 3 年
Normative: 1.5 years; Maximum: 3 years
3 年，最长不超过 4.5 年
Normative: 3 years; Maximum: 4.5 years 学习周期 Study Period
全日制 Full-time 非全日制 Part-time
Taught Postgraduate Programmes Master of Science in Bioinformatics
32 School of Data Science
MASTER OF SCIENCE IN ARTIFICIAL
INTELLIGENCE AND ROBOTICS
人工智能与机器人理学硕士
The School of Data Science (SDS) and the School of Science and Engineering
(SSE) at The Chinese University of Hong Kong, Shenzhen jointly offer a
two-year Master's program in Artificial Intelligence and Robotics, with two
concentrations: Artificial Intelligence and Robotics. The program leverages
the excellent faculty and research capabilities of SDS, SSE and the Shenzhen
Institute of Artificial Intelligence and Robotics for Society to cultivate cuttingedge talents in these fields. Students will acquire a solid grasp of fundamental
theories in computer science, artificial intelligence, and robotics, and will
delve deeply into topics such as machine learning, computer vision, natural
language processing, robotics, automation, intelligent systems, and humanmachine interaction.
Before graduation, students are presented with invaluable opportunities to
actively participate in capstone projects. These projects involve collaborations
with renowned international universities and esteemed domestic enterprises,
thereby honing their practical skills and fortifying their problem-solving
capabilities. By engaging in such endeavors, students are thoroughly prepared
for their future academic pursuits or professional endeavors. Following
graduation, they emerge as accomplished professionals in the realm of
artificial intelligence and robotics, driving the rapid growth of information
technology in the Guangdong-Hong Kong-Macao Greater Bay Area and the
nation as a whole.
人工智能与机器人理学硕士项目是由香港中文大
学（深圳）数据科学学院和理工学院共同开设。学制
为两年，并提供两个细分方向供学生选择：人工智能
和机器人。本项目依托港中大（深圳）数据科学学院、
理工学院及深圳市人工智能与机器人研究院的优秀师
资和科研力量，旨在培养人工智能与机器人领域的尖
端人才。学生将掌握计算机科学、人工智能和机器人
领域的基本理论，并在机器学习、计算机视觉、自然
语言处理、机器人、自动化、智能系统和人机交互等
领域深入学习。
毕业前，学生将有机会参与到实际研究课题项目
中，包括与海外知名大学、国内知名企业合作，提高
实践技能和解决问题的能力，为未来深造或就业做好
充足准备。毕业后，学生将成为人工智能和机器人领
域的专业人才，为粤港澳大湾区和整个国家信息技术
快速发展助力。
世界一流的导师团队，
院士会士尖端人才云集
学科前沿，涵盖人工智能
与机器人两大热门科技领域
国际化教学水平与氛围，
全英文授课
业界、研究院联系紧密，
丰富的交流与实践机会
紧贴国家人才发展战略，
高薪酬、就业前景好
香港中文大学学位证书，
教育部留学服务中心学历学位认证
World-Class Mentors:
Gathering Distinguished Scholars
and Leading Experts
Strong Connections with Industry
and Research Institute: Rich
Opportunities for Practice
Cutting-Edge Disciplines:
Covering Thriving Fields of AI
and Robotics
Aligned with National Science and
Technolgy Development Strategy:
Excellent Job Prospects
CUHK Degree Certificate:
Recognized by Ministry of
Education
English Immersion Teaching:
Fostering an Internationalized
Education Environment
FACULTY 项目师资
Taught Postgraduate Programmes Master of Science in Artificial Intelligence And Robotics
教授，博士（哥伦比亚大学）
研究领域：机器学习/数据挖掘、生物信息学、
信息检索、网络链接分析、高性能计算
Professor, Ph.D. (Columbia University)
Research Field: Machine Learning, Data Mining,
Bioinformatics, Information Retrieval,
Web Link Analysis, High Performance Computing
丁宏强 DING, Hongqiang
港中大（深圳）协理副校长（拓展事务），
教授，国际电气电子工程师学会会士，
博士（美国西北大学）
研究领域：群体智能、网络优化和经济学
Associate Vice President (Institutional
Development), Professor, IEEE Fellow,
Ph.D. (Northwestern University, USA)
Research Field: Crowd intelligence,
network optimization and economics
黄建伟 HUANG, Jianwei
教授，国际电气电子工程师学会会士，亚太人工智
能学会会士，博士（加利福尼亚大学伯克利分校）
研究领域：计算机体系结构、并行处理、网络安全、
云计算和物联网
Professor, IEEE Life Fellow, Fellow of the
Asia-Pacific Artificial Intelligence Association,
Ph.D. (University of California, Berkeley)
Research Field: Computer Architecture, Parallel
Processing, Network Security, Cloud Computing and IoT
黄铠 HWANG, Kai
副教授，博士（罗格斯大学）
研究领域：计算机视觉、图像处理、模式识别、
机器学习
Associate Professor, Ph.D. (Rutgers University)
Research Field: Computer vision, image processing,
pattern recognition, machine learning
黄锐 HUANG, Rui
数据科学学院执行院长，教授，新加坡工程院院士，
国际电气电子工程师学会会士，亚太人工智能学会
会士，博士（华南理工大学）
研究领域：语音信息处理、自然语言处理、
类脑计算、人机交互
Executive Dean, Professor, Fellow of the Academy
of Engineering, Singapore, IEEE Fellow, Fellow of
the Asia-Pacific Artificial Intelligence Association,
Ph.D. (South China University of Technology)
Research Field: Speech Information Processing,
Natural Language Processing, Neuromorphic Computing,
Human-Computer Interface
李海洲 LI, Haizhou
人工智能与机器人硕士项目联合主任，副教授，
博士（香港中文大学）
研究领域：机器学习、人工智能、凸优化、
概率推理
Co-Director of M.Sc. in Artificial Intelligence
and Robotics Program, Associate Professor,
Ph.D. (The Chinese University of Hong Kong)
Research Field: Machine Learning,
Artificial Intelligence, Convex Optimization,
and Probabilistic Inference
李文烨 LI, Wenye
助理教授，博士（香港中文大学）
研究领域：多机器人系统、野外机器人、协作机器人
Assistant Professor, Ph.D. (The Chinese University
of Hong Kong)
Research Field: Multi-robot systems, field robotics,
collaborative robotics
林天麟 LAM, Tin Lun
香港中文大学（深圳）副校长，教授，中国工程
院外籍院士，加拿大皇家科学院院士，国际电气
电子工程师学会会士，美国工业与应用数学学会
会士，博士（麻省理工学院）
研究领域：大数据分析的最优化方法、信号处理中
的算法设计与复杂性分析、数据通信
罗智泉 LUO, Zhiquan
助理教授，博士（香港中文大学）
研究领域：机器人、智能系统
Assistant Professor, Ph.D. (The Chinese University
of Hong Kong)
Research Field: Robotics, intelligent systems
钱辉环 QIAN, Huihuan
教授（兼职），美国工程院院士，美国艺术与科学
院院士，博士（日本京都大学）
研究领域：计算机视觉、机器人
Professor (Adjunct), Member of the National
Academy of Engineering (USA), Member of the
American Academy of Arts and Sciences,
Ph.D. (Kyoto University, Japan)
Research Field: Computer vision, Robotics
KANADE, Takeo
副教授，博士（香港科技大学）
研究领域：分布式系统、网络控制系统、卡尔曼滤波，
信号处理、信息物理系统安全与隐私
Associate Professor, Ph.D. (The Hong Kong
University of Science and Technology)
Research Field: Distributed Systems, Control Network
Systems, Kalman Filtering, Signal Processing,
Cyber Security and Privacy
吴均峰 WU, Junfeng
香港中文大学（深圳）校长，教授，中国工程院院士，
美国国家工程院外籍院士，博士（宾夕法尼亚大学）
研究领域：机器人、智能系统与控制、设计与制造、空间机
器人、服务机器人、穿戴式人机界面、智慧混合动力汽车等
President, Professor, Academician of Chinese Academy
of Engineering, International Member of the US National
Academy of Engineering, Ph.D. (University of Pennsylvania)
Research Field: Robotics, intelligent systems and control,
design and manufacturing, service and space robotics,
wearable interface, intelligent electric vehicles
徐扬生 XU, Yangsheng
Vice President, Professor, foreign member of the
Chinese Academy of Engineering (CAE), Fellow of
the Royal Society of Canada, IEEE Fellow, Fellow of
the Society for Industrial and Applied Mathematics,
Ph.D. (Massachusetts Institute of Technology)
Research Field: Optimization methods for big data
analytics, complexity and computational issues arising
from signal processing, digital communication
sds.cuhk.edu.cn 33
34 School of Data Science
人工智能与机器人硕士项目联合主任，助理教授，
博士（香港中文大学）
研究领域：微/纳米机器人、医疗机器人、生物医学
Co-Director of MSc in Artificial Intelligence and
Robotics Program, Assistant Professor,
Ph.D. (The Chinese University of Hong Kong)
Research Field: Micro/nanorobotics, medical robotics,
biomedicine
俞江帆 YU, Jiangfan
数据科学学院副院长（科研），教授，
博士（斯坦福大学）
研究领域：机器学习及应用
Associate Dean (Research), Professor,
Ph.D. (Stanford University)
Research Field: Machine Learning and Applications
查宏远 ZHA, Hongyuan
教授，加拿大工程院院士，加拿大皇家科学院院
士，国际电气及电子工程师学会会士，国际模式
识别协会会士，亚太人工智能学会会士，
博士（哈尔滨工业大学、滑铁卢大学）
研究领域：模式识别、图像处理、生物特征识别
Professor, Fellow of the Canadian Academy of
Engineering, Fellow of the Royal Society
of Canada, IEEE Life Fellow, IAPR Fellow
Fellow of the Asia-Pacific Artificial
Intelligence Association,
Ph.D. (Harbin Institute of Technology,
University of Waterloo)
Research Field: Pattern Recognition,
Image Processing and Biometrics
张大鹏 ZHANG, Dapeng
教授，新加坡工程院院士，
国际电气电子工程师学会会士，
博士（斯坦福大学）
研究领域：无线通信
Professor, Fellow of the Academy of Engineering,
Singapore, Fellow of the IEEE,
Ph.D. (Stanford University)
Research Field: Wireless communications
张瑞 ZHANG, Rui
教授，美国工业与应用数学学会会士，
博士（纽约州立大学石溪分校）
研究领域：最优化算法的设计分析以及数值实现、
最优化算法在各领域的应用、在数据科学、
图像与信号处理、机器学习等领域的应用
Professor, Fellow of the Society for Industrial
and Applied Mathematics,
Ph.D. (State University of New York, Stony Brook)
Research Field: Numerical Optimization, Algorithm
Design, Analysis and Implementation, Applications
of Optimization in Various Areas, particularly in Data
Science, Image/Signal Processing and Machine Learning
张寅 ZHANG, Yin
教授，博士（雪城大学）
研究领域：云雾计算与大数据、嵌入式系统、
并行与分布式系统
Professor, Ph.D. (Syracuse University)
Research Field: Cloud-Fog Computing, Big Data,
Embedded Systems, Parallel and Distributed Systems
钟叶青 CHUNG, Yeqing
副教授，博士（加拿大阿尔伯塔大学）
研究领域：软体智能机器人、仿生机器人及智能材料
和结构
Associate Professor,
Ph.D. (University of Alberta, Canada)
Research Field: Intelligent soft robots, Bioinspired robots,
Smart materials and structures
朱建 ZHU, Jian
Taught Postgraduate Programmes Master of Science in Artificial Intelligence And Robotics
sds.cuhk.edu.cn 35
人工智能与机器人领域就业前景 EMPLOYMENT PROSPECTS IN THE FIELD OF
ARTIFICIAL INTELLIGENCE AND ROBOTICS
从 2019 年起至 2021 年，人工智能、生产制造、大数据、能源环保、医疗健康等行业招聘需求呈现持续爆发之势。
其中，人工智能领域 2021 年同比增长 51.39%，大数据行业 2021 年同比增长 32.57%。
From 2019 to 2021, there has been an exponential surge in recruitment demands for industries such as artificial intelligence,
manufacturing, big data, energy conservation and environmental protection, and healthcare. Notably, the field of artificial intelligence
experienced a remarkable year-on-year growth of 51.39% in 2021, while the big data industry witnessed a growth of 32.57%.
人工智能行业中高端人才平均年薪最高，IT 互联网行业中高端人才平均年薪 23.02 万元。
The field of artificial intelligence presents the highest average annual salary for mid- and high-end talents, with IT and Internet
professionals earning an average annual salary of 230,200 RMB.
猎聘《2022 未来人才就业趋势报告》
According to the 2022 Future Talent Employment Trends Report by Liepin
2019 年以来新发职位同比增长较快的五大领域
Top Five Fields with Rapid Year-on-Year Growth in Newly Created Positions Since 2019
2022.1-4 月中高端人才薪资 TOP10 行业及较 2018 年同期薪资上涨情况
Top 10 Industries: Min- and High-End Talent Salaries (Jan-Apr 2022) and Increase Compared to 2018
数据来源 : 猎聘大教据 Source: Liepin Big Data
数据来源 : 猎聘大教据 Source: Liepin Big Data
人工智能
Artificial Intelligence
60.00%
50.00%
40.00%
30.00%
20.00%
10.00%
0.00%
2019 2020 2021
4.88%
12.20%
28.12%
51.39%
38.73%
32.57%
30.26%
26.10%
14.09% 15.44%
13.96%
生产制造
Manufacturing
大数据
Big Data
医疗健康
Healthcare
能源环保
Energy Conservation, and Environmental Protection
16.66%
21.39%
28.88%
32.88%
行业 Industry
年薪排名
Salary
Ranking
2022.1-4 月人才平均年薪
Average Annual Salary in
January-April 2022
( 单位：万元 ) (in 10,000 RMB)
2018.1-4 月人才平均年薪
Average Annual Salary in
January-April 2018
( 单位：万元 ) (in 10,000 RMB)
五年来，薪资上涨差值
Salary Increase over
Five Years
( 单位：万元 ) (in 10,000 RMB)
人工智能 Artificial Intelligence 1 31.04 26.43 4.61
金融 Finance 2 27.69 21.91 5.78
通信 Communication 3 27.51 24.23 3.27
大数据 Big Data 4 25.23 20.36 4.87
游戏 Gaming 5 24.25 19.66 4.60
房地产业 Real Estate 6 23.98 20.83 3.16
IT/ 互联网 IT/Internet 7 23.02 18.91 4.11
消费品 Consumer Goods 8 22.34 18.62 3.27
文体传媒 Media and Entertainment 9 21.66 18.57 3.09
汽车交通 Automotive and Transportation 10 21.59 16.97 4.62
36 School of Data Science
课程设置 CURRICULUM
学生需在学习周期中完成 6 门必修课程和 4 门选修课程，并在学术和 / 业界导师的指导下完成研究课题。每门课程有 3 学分。
研究课题有 6 个学分。修满 36 学分并符合其他毕业条件的学生方能毕业。
Students need to complete 6 required courses and 4 elective courses offered in the regular terms within the normative study period,
and completing a Capstone Project supervised by academic faculty/ industrial supervisors. Each course carries 3 credits. The Capstone
project carries 6 credits. Students should complete total 36 credits in order to graduate.
人工智能与机器人理学硕士项目 M.Sc. in Artificial Intelligence and Robotics (MAIR)
全日制 Full-time
学位 Degree Awarded 香港中文大学理学硕士学位证书 Master of Science The Chinese University of Hong Kong
学制 Mode of Study
学期 Program Duration 2 年 2 years
授课语言 Language 英文 English
学分要求 Credit Requirement 共 36 专业学分 36 credits in total
学费 Tuition Fees 288,000 元人民币 RMB 288,000
入学奖学金：10 万 /5 万 /3 万人民币 学业奖学金
Admission Scholarship: RMB100,000/50,000/30,000 Academic Scholarship 奖学金 Scholarships
人工智能与机器人硕士项目
研究课题（6 学分）
选修课
（12 学分）
方向必修课
（9 学分）
公共必修课
（9 学分）
人工智能方向 机器人方向
语音信息处理
人机交互
虚拟现实与元宇宙
强化学习
计算理论
并行与分布式计算
软件工程
系统与控制
机器人设计与制造
移动机器人
微纳米机器人
软体机器人
机器人触觉导论
工程材料
信号处理高级专题
人工智能专题选讲
人工智能的安全与隐私
云计算
自然语言处理
马尔可夫链蒙特卡洛方法等
深度学习
高级数据库系统
优化理论与算法 机器人操作
图像处理与计算器视觉
机器人数学基础
高级人工智能 高级机器学习 高级计算机算法
M.Sc. in Artificial Intelligence and Robotics (MAIR)
Concentration: Artificial Intelligence Concentration: Robotics
Concentration-specific
Required Courses
(9 units)
Deep Learning
Advanced Database Systems
Optimization Theory and Algorithms
Robot Manipulation
Image Processing and Computer Vision
Math Fundamentals for Robotics
Capstone project (for both concentrations) (6 units)
Elective Courses
(12 units)
Markov Chain Monte Carlo
Methods
Spoken Language Processing
Human-Machine Interaction
Virtual Reality and Metaverse
Reinforcement Learning
Theory of Computation
Parallel and Distributed
Computing
Advanced Topics in Signal
Processing
Selected Topics in Artificial
Intelligence
AI Security and Privacy
Cloud Computing
Natural Language Processing
Software Engineering
System and Control
Robot Design and
Manufacturing
Mobile Robotics
Micro-Nanorobotics
Soft Robotics
Introduction to Haptics
Engineering Materials
General Required Courses
(for both concentrations) (9 units)
Advanced Artificial
Intelligence
Advanced Computer
Algorithms
Advanced Machine
Learning
申请材料
1. 学历证明
本科生毕业证、学位证或在读证明
2. 大学成绩单原件
需教务处或学院盖章，其中需列明全部曾修读的科目及考试
成绩。如成绩表未注明均分或成绩等级，则需提供均分证明。
（中文或英文，盖有毕业院校公章）
3. 英语能力考试成绩单原件
雅思、托福或 GMAT
4. 个人简历（英文）和个人陈述
英文，600 字左右
5. 身份证正反面扫描件
6. 两封推荐信
7. 其他支持性文件
如有需要，或会要求申请人提交补充资料或证明文件
Application Materials
1. A copy of Bachelor's and/or Master's Degree Certificate or
Student Status Certificate
2. A copy of transcript (Official document from the academic
affairs office or college, stamped or sealed, indicating all courses
taken and corresponding grades. If the transcript does not
indicate the overall GPA or grading system, a separate document
certifying the GPA is required. In Chinese or English, with the
official seal of the undergraduate institution.)
3. A copy of TOEFL/IELTS/GMAT score sheet
4. Curriculum Vitae (CV) and Personal Statement
(Written in English, approximately 600 words)
5. A copy of ID card (Front & Back)
6. Contact details of two referees
7. Other supporting documents
申请要求
具有理工科专业背景的申请人优先考虑，欢迎跨专业报考。
申请人需满足下列要求：
- 毕业于国家教育部认可的大学或机构，具有学士学位，成绩
不低于二等荣誉学士，或
- 毕业于认可的大学或机构，具有学士学位，成绩不低于“B”
（GPA3.0/4.0 或 80/100 分 )，或
- 完成高等教育课程的学习，具有相当于学士学位的资历
申请人需提交英语水平证明文件：
符合以下要求之一
1. 托福（网考不低于 79 分）；
2. 雅思（学术类）（不低于 6.5 分）；
3. 研究生管理科学入学考试 GMAT（阅读）（不低于 21 分）；
4. 获得香港或英语为母语国家及地区的相关学位或专业证书。
Application Requirements
The applicant should either:
- Graduated from a university or institution recognized by
the Ministry of Education, with a bachelor's degree, with a
minimum grade equivalent to Second Class Honors, or
- Graduated from a recognized university or institution, with a
bachelor's degree, with a minimum grade of “B” (GPA 3.0/4.0
or 80/100), or
- Completed equivalent higher education coursework, with
qualifications equivalent to a bachelor's degree.
The applicant should either:
1. TOEFL (Not lower than 79 internet-based),
2. IELTS (Academic, not lower than Band 6.5),
3. GMAT (Verbal, not lower than 21),
4. Obtained a relevant degree or professional certificate from
Hong Kong or an English-speaking country or region.
* Note:
a.TOEFL and IELTS scores are valid for two years from the date of the
test; GMAT scores are valid for 5 years from the date of the test.
申请信息
网申地址：https://pgapply.cuhk.edu.cn/
报名费：申请费为人民币 300 元（一经缴费，不设退费）
Application Information
Online application: https://pgapply.cuhk.edu.cn/
The application fee is RMB300 and is non-refundable once paid.
申请时间
首轮申请时间：
2023 年 5 月 20 日 -2023 年 6 月 15 日
二轮申请截止时间：
2023 年 7 月 15 日
Application Time
First Round Application Period:
May 20, 2023- June 15, 2023
Second Round Application Deadline:
July 15, 2023
sds.cuhk.edu.cn 37
Taught Postgraduate Programmes Master of Science in Artificial Intelligence And Robotics
数据科学学院数据科学博士专业旨在培养学术成绩优异且有高度进取心的数据科学相关领域的高级
研究性人才，所涵盖的研究领域包括：运筹学、统计学、运营管理和决策科学、机器学习及相关交叉领域。
数据科学博士项目的学生将有机会参与本校与深圳市大数据研究院和深圳市人工智能与机器人研究院的
研究工作。我院旨在培养最优秀的博士生，毕业后有能力进入顶尖研究型大学任教或进入业界最先进的
研发实验室工作。学生可通过网申系统或招生夏令营进行项目申请。
The School of Data Science (SDS) has designed the programme for exceptionally motivated and
mathematically talented students who wish to pursue a higher degree in the interdisciplinary research
areas of Data Science, Operations Research and Management, Statistics, Optimization and Machine
Learning. Admitted students will have opportunities to work at Shenzhen Research Institute of Big
Data (SRIBD) or Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS). SDS aims
to produce the best-trained Ph.D. students who will be capable of becoming faculty members at top
research universities or working in leading research and development labs in industry. Students can
apply for the programme through online application system and admission summer camp.
DATA SCIENCE
PH.D. PROGRAMME IN
38 School of Data Science
RESEARCH POSTGRADUATE
PROGRAMME 博士项目
数据科学博士
A 组课程 Group A Courses
随机过程
优化理论与算法
Stochastic Processes
Optimization Theory and Algorithms
基于测度理论的概率论
高级统计理论
Measure Theoretic Probability
Advanced Statistics Theory
算法分析
机器学习
Analysis of Algorithms
Machine Learning
授课课程 CURRICULUM
sds.cuhk.edu.cn 39
香港中文大学（深圳）将为优秀的申请人提供学费减免和各类奖学金支持。
奖学金总金额可高达人民币 150 万 （含五年学费、生活费及国外交流补贴）。
CUHK-Shenzhen may offer tuition waiver and various kinds of financial supports to
selected applicants. The fellowship could be up to RMB 1.5 million in total
(including 5 years' tuition, stipend and oversea exchange travelling allowance).
更多招生信息请登录：
https://sds.cuhk.edu.cn/phd-programmes
More Information:
https://sds.cuhk.edu.cn/en/phd-programmes
Research Postgraduate Programme Ph.D. Programme in Data Science
Dynamic Programming and
Stochastic Control
Simulation
Reinforcement Learning
Advanced Machine Learning
Advanced Data Management
Advanced Convex Optimization
Discrete Optimization
Stochastic Optimization
AI security and privacy
Optimization Models and Methods
in Machine Learning
Selected Topics in Data and
Decision Analytics
Advanced Optimization
Revenue Management
Game Theory and Its Applications
Selected Topics in Deep Learning
Embedded Systems
Advanced Database Systems
Virtualization Techniques
Cloud Computing
Graph Computing
GPU Programming
Natural Language Processing
Computational Methods and Tools
for Data and Decision Analytics
Advanced Applied Statistics
and Data Analysis
Selected Topics in Statistics
Matrix Analysis
Image Processing and
Computer Vision
Selected Topics in Information
Theory
Regularization/Kernel Methods:
Theory for the Users
Probabilistic Graphical Models
Computational Imaging
动态规划与随机控制
模拟学
强化学习
高级机器学习
高级数据管理
高级凸优化
离散优化
随机优化
人工智能的安全与隐私
机器学习中的优化模型和方法
数据和决策分析专题
高级优化
收益管理
博弈论及其应用
深度学习专题
嵌入式系统
高等数据库系统
B 组课程 Group B Courses
虚拟化技术
云计算
图计算
图形处理器编程
文本表征学习
数据及决策分析的计算
方法及工具
高等应用统计及资料分析
统计学专题
矩阵分析
图像处理与计算机视觉
信息论专题
正规化方法和核方法：
使用者的理论
概率图形模型
计算成像
1. Graduated from a recognized
university and obtained a Bachelor’s/
Master's degree, normally with
honours not lower than Second
Class; or achieve an average grade
of not lower than “B”. Or obtained
professional or similar qualifications
equivalent to an honors degree.
2. Fulfilled the English Language
Proficiency Requirement as specified
below:
2.1 TOEFL (not lower than 550
paper-based; 213 computer-based;
and 79 internet-based); or
2.2 IELTS (Academic) (not lower than
Band 6.5); or
2.3 have obtained a recognized
professional qualification awarded in
Hong Kong or an English-speaking
country.
There will be an interview
administered by the Programme.
Minimum Entry Requirement
对于攻读博士学位的申请人，需满足： All applicants must fulfill the following qualifications for admission:
1. 毕业于认可的大学或机构，具有硕士或学
士学位，成绩不低于二级荣誉或不低于“B”，
或同等学历。
2. 英语要求（符合以下要求之一）
申请条件
2.1 托福：机试不低于 213 分；
网考不低于 79 分；笔试不低于 550 分；
2.2 雅思（学术类）：不低于 6.5 分；
2.3 获得香港或英语为母语国家的学校颁发
的相关学位或专业证书；
Note: TOEFL and IELTS scores are considered valid for two years from the test date.
备注：托福和雅思成绩自考试之日起两年有效。
数据科学博士项目组将视情况对申请人进行面试。
40 School of Data Science
PH.D. PROGRAMME IN
COMPUTER SCIENCE
计算机科学博士
计算机科学博士专业旨在培养面向基础与应用科学技术问题，具备创
新能力、科学抱负、人生理想及国际化视野，且脚踏实地不懈奋斗的计算
机科学领域的研究类和应用类人才。本专业所涵盖的学术领域包括：计算
机基础理论、人工智能与机器学习、计算机系统与网络、多媒体与人机接口、
数据库与软件工程、计算机图形学与可视化、云计算、计算机安全、智能
控制及相关交叉领域。入读本专业的学生，有机会参与本校与深圳市大数
据研究院、深圳市人工智能与机器人研究院、以及多家业界联合实验室的
研究工作。优秀的博士生毕业后，可进入研究型大学任教或进入业界领先
的公司和实验室工作，成为推动及引领信息技术发展的高级专业人才和核
心力量。
The programme is designed for exceptionally motivated and
mathematically talented students who wish to pursue a higher degree in
the interdisciplinary research areas of Data Science, Operations Research
and Management, Statistics, Computer Science, Optimization and
Machine Learning. Admitted students will have opportunities to work at
Shenzhen Research Institute of Big Data (SRIBD) or Shenzhen Institute of
Artificial Intelligence and Robotics for Society (AIRS). SDS aims to produce
the best-trained Ph.D. students who will be capable of becoming faculty
members at top research universities or working in leading research and
development labs in the industry.
A 组课程 Group A Courses
算法分析
计算理论
优化理论与算法
人工智能
机器学习
高等计算机体系结构
Analysis of Algorithms
Theory of Computation
Optimization Theory and Algorithms
Artificial Intelligence
Machine Learning
Advanced Computer Architecture
高等操作系统
软件工程
高等数据库系统
图像处理与计算机视觉
自然语言处理
Advanced Operating System
Software Engineering
Advanced Database Systems
Image Processing and Computer Vision
Natural Language Processing
授课课程 CURRICULUM
sds.cuhk.edu.cn 41
香港中文大学（深圳）将为优秀的申请人提供学费减免和各类奖学金支持。
奖学金总金额可高达人民币 150 万 （含五年学费、生活费及国外交流补贴）。
CUHK-Shenzhen may offer tuition waiver and various kinds of financial supports to
selected applicants. The fellowship could be up to RMB 1.5 million in total
(including 5 years' tuition, stipend and oversea exchange travelling allowance).
更多招生信息请登录：
https://sds.cuhk.edu.cn/phd-programmes-CSE
More Information:
https://sds.cuhk.edu.cn/en/phd-programmes-CSE
1. Graduated from a recognized
university and obtained a
Bachelor’s/Master's degree,
normally with honours not lower
than Second Class; or achieve an
average grade of not lower than
“B”. Or obtained professional or
similar qualifications equivalent to
an honors degree.
2. Fulfilled the English Language
Proficiency Requirement as
specified below:
2.1 TOEFL (not lower than 550
paper-based; 213 computer-based;
and 79 internet-based); or
2.2 IELTS (Academic) (not lower
than Band 6.5); or
2.3 GMAT: Band 21 (Verbal)
2.4 have obtained a recognized
professional qualification awarded
in Hong Kong or an Englishspeaking country.
There will be an interview
administered by the Programme.
Minimum Entry Requirement
All applicants must fulfill the following qualifications for admission:
Note: TOEFL and IELTS scores are considered valid for two years from the test date.
GMAT scores are considered valid for five years from the test date.
对于攻读博士学位的申请人，需满足：
1. 毕业于认可的大学或机构，具有硕士或学
士学位，成绩不低于二级荣誉或不低于“B”，
或同等学历。
2. 英语要求（符合以下要求之一）
申请条件
2.1 托福：机试不低于 213 分；
网考不低于 79 分；笔试不低于 550 分；
2.2 雅思（学术类）：不低于 6.5 分；
2.3 GMAT: Band 21 (Verbal)
2.4 获得香港或英语为母语国家的学校颁发的
相关学位或专业证书；
备注：托福和雅思成绩自考试之日起两年有效。
GMAT 成绩自考试之日起 5 年内有效。
计算机科学博士项目组将视情况对申请人进行面试。
Embedded Systems
Real-Time Systems
Virtualization Techniques
Advanced File and Storage Systems
Computer and Network Security
Blockchain Systems
GPU Programming
Mobile Computing
Cloud Computing
Robotics and Intelligent Systems
Advanced Data Management
Social Computing
Automated Software Testing
and Analysis
Virtual Reality
Parallel Programming
Computer Graphics
Human-Computer Interaction
Information Theory
Matrix Analysis
Simulation
Dynamic Programming and
Stochastic Control
Advanced Convex Optimization
Stochastic Processes
Graph Computing
Privacy, Fairness and
Accountability of Algorithms
Advanced Machine Learning
Data Analytics
Techniques for Data Mining
Reinforcement Learning
Regularization/Kernel Methods:
Theory for the Users
Probabilistic Graphical Models
Computational Methods and Tools
for Data and Decision Analytics
Deep Learning
Advanced Algorithms
Computational Imaging
Selected Topics in CS
嵌入式系统
及时系统
虚拟化技术
高等文档与存储系统
计算机与网络安全
区块链系统
图形处理器编程
移动计算
云计算
机器人智能系统
高级数据管理
社交计算
自动化软件测试与分析
虚拟实境
并行计算
计算机图形学
人机互交
信息论
矩阵分析
B 组课程 Group B Courses
模拟学
动态规划与随机控制
高等凸优化
随机过程
图计算
算法隐私性、公平性和
可问责性
高级机器学习
数据分析
数据挖掘技术
强化学习
正规化方法和核及方法：
使用者的理论
概率图形模型
数据及决策分析的计算
方法及工具
深度学习
高级算法
计算成像
计算机专题
Research Postgraduate Programme Ph.D. Programme in Computer Science
42 School of Data Science
ACADEMIC
ACHIEVEMENTS 学术成就
科研项目
2020 年至今，数据科学学院共获批 60 个
国家、省市、区级科研项目，其中国家自然
科学基金项目共 32 项，基金总额逾千万，
其中 1 项“原创探索计划”为学校首例。
国家自然科学基金原创探索计划项目：数据缺
乏和模型变化下的在线机器学习和优化算法
7 项国家自然科学基金面上项目：
1）基于统一数学化描述的深度学习系统对
抗性现象研究
2）大规模非接触式多模态掌纹识别研究
3）数据驱动的排队系统在线优化算法研究
4）核正则化系统辨识的若干关键问题研究
5）面向复杂声学场景的类脑说话人提取模
型与算法研究
6）特殊欧氏群的卡尔曼滤波理论及其在同
时定位与建图中的应用
7）行为金融框架下的资产配置与择时及定
价问题研究
22 项国家自然科学基金青年科学基金项目：
1）分布式随机优化的渐近网络无关性研究
2） 不 可 逆 Markov 链 的 Metropolis -
Hastings 可逆化
3）时序模型选择后的参数估计及有效推断
4）到达过程具有自相关性的排队模型
5）大维非中心化 Fisher 矩阵的谱分析及
其应用
6）基于展望理论的赌徒停时策略问题的研究
7）基于边界注意力水平集的医学图像分割
关键技术研究
8）基于深度学习及数据驱动的全景图像编码
9）基于自动化日志分析的大规模软件可靠
性工程研究
10）面向大规模复杂异质图的稠密子图搜
索研究
11）快速非凸非光滑张量恢复的模型、算法、
理论和应用
12）基于泛函机制的强化学习隐私保护算
法研究
13）直播购物中具备内生信息设计的位置
拍卖理论
14）可解释逻辑点过程及其在复杂时序系
统中的应用
15）非光滑非凸优化中的一类随机模型算
法和应用研究
16）面向 6G 泛在感知的语义通信与自组
网融合方法研究
17）多表型单细胞转录组测序的实验设计
和统计建模
18）数据驱动的森林火灾应急管理协调运
营的优化方法研究
19）考虑用户行为的网约车派单匹配机制
研究
20）脉搏波信号智能化采集关键技术研究
21）基于机器学习核正则化方法的线性时
变系统数据驱动控制技术研究
22）面向大规模有向图的高效稠密子图挖
掘算法研究
2 项国家自然科学基金外国学者研究基金
项目 :
1）几类求解结构性随机变分不等式的高阶
优化算法的设计和分析
2）在人工神经网络的部分训练中随机梯度
下降被证明能避免所有“不良的”非全局最
优的局部极小值点
4 项广东省基础与应用基础研究基金自然科
学基金面上项目：
1）面向大规模有向图的高效最密子图挖掘
算法研究
2）基于海量图文表达预训练的分层视觉内
容理解关键技术研究
3）面向大数据处理的数据升维模型、算法
及应用研究
4) 基于异构计算的大规模图的子图计数算
法与应用研究
广东省重点领域研发计划：基于可敏捷定制
处理器的云雾平台项目
广东省基础与应用基础研究 - 粤深联合基
金青年基金项目：
1) 无人机辅助的移动边缘网络中路径规划
与计算机卸载研究
2) 一类可分割的回收品共享平台资源优化
研究：联盟合作视角
广东省基础与应用基础研究 - 粤深联合基
金重点项目：手指多模态特征提取与识别
广东省基础与应用基础研究 - 广东省自然
科学基金：基于展望理论的时间不一致风险
偏好下的赌徒决策问题研究
广东省大数据计算基础理论与方法重点实验
室资助：
1）大数据的版权与隐私保护研究
2）基于多模态生理信号的听觉认知分析
3）基于多智能体强化学习的协同决策机制
及其在机场群系统中的应用
4）电子商务中的在线算法研究
2 项深圳市基础研究重点项目：
1）极端环境下机器人传感退化机理与感知
定位方法研究
2) 多模态数据和多任务深度网络构建与训
练研究
3 项深圳市基础研究面上项目：
1）面向电商知识图谱的异常行为检测方法
研究
2）核正则化线性系统辨识的若干关键问题
研究
3）基于移动边缘多智能体的 6G 空天地融
合感知关键技术研究
深圳基础研究专项（自然科学基金）高等院
校稳定支持计划：机器学习中最优化算法与
应用
深圳市技术创新资助项目：计算机同声传译
系统的研究及开发
深圳市协同创新计划【实验室开放基金项
目】：跨模态半监督深度哈希行人重识别关
键技术研究
深圳市优秀科技创新人才培育计划【深圳市
博士基础科研启动项目】
1）一类非下降坐标法的设计与分析及其在
非光滑优化中的应用
2）基于泛函分析的强化学习隐私保护机制
研究
深圳市优秀科技创新人才培育计划【深圳市
优秀青年基础科研项目】
1）复杂排队系统的在线随机优化算法与理论
2）人工智能安全原理、算法及标准化平台
研究
3）多智能体网络中的分布式随机优化
深圳市知识创新计划【深圳市基础研究（自
由探索）】：面向医疗与健康服务的人机自
然语言对话系统研究及实现
深圳市知识创新计划【深圳市基础研究（学
科布局）】：时空大数据的统计建模理论与
分布式优化方法研究
sds.cuhk.edu.cn 43
Academic Achievements
广东省重点实验室
广东省大数据计算基础理论与方法重点实验室
广东省人工智能数理基础重点实验室
深圳市重点实验室
深圳市模式分析与感知计算重点实验室（筹
建启动）
企业联合实验室
港中大（深圳）- 联易融计算机视觉与人工
智能联合实验室
学术论文
学院 2020 年成立至今，数据科学学院教授
团队在众多国际知名会议及顶级期刊上发表
了 328 余篇高质量论文。
专著
• 张大鹏教授 -《Information Fusion:
Machine Learning Methods》
（合著者：李锦兴、Bob Zhang）和
《Advanced Fingerprint Recognition:
From 3D Shape to Ridge Detail》
（合著者：Feng Liu、Qijun Zhao）
• 戴 建 岗 教 授 -《Processing Networks
Fluid Models and Stability》（合著者：J.
Michael Harrison）
• 陈 天 石 教 授 -《Regularized System
Identification: Learning Dynamic
Models from Data》（合著者：Gianluigi
Pillonett、Alessandro Chiuso、
Giuseppe De Nicalao、Lennart Ljung）
• 黄建华教授 -《A New Model of Capital
Asset Prices: Theory and Evidence》（合
著者：James W. Kolari, Wei Liu）
• 方 一 向 教 授 -《Cohesive Subgraph
Search Over Large Heterogeneous
Information Networks》（ 合 著 者：Kai
Wang, Xuemin Lin, Wenjie Zhang）
• 王子卓教授 -《The Elements of
Joint Learning and Optimization in
Operations Management》
（合著者：Qi Chen, He Wang）
奖项 / 荣誉（部分）
• 张寅教授荣获国际数学优化学会“Paul Y.
Tseng 纪念奖”
• 李海洲教授团队荣获“VoxSRC-22 说话
人识别挑战赛”第二名
• 王本友教授荣获“NLPCC 2022 最佳论文
奖”
• 陈天石教授获评 2022 深圳市教育工作先
进个人荣誉称号
• 蔡小强、黄铠、李海洲、张大鹏 4 位教授
当选亚太人工智能学会会士
• 黄 建 华 教 授 荣 获 2022 年“INFORMS
Impact Prize”
• 李 海 洲 教 授 团 队 论 文 荣 获“Oriental
COCOSDA 2022 最佳论文奖”
• 蔡小强、陈天石、Konstantinos
Courcoubetis、丁宏强、Guillermo
Gallego、贺品嘉、黄建华、黄铠、Arnulf
Jentzen、李海洲、罗智泉、吴保元、武执
政、严明、查宏远、张大鹏、张寅共 17 位
教授上榜“全球 Top 2% 顶尖科学家”
• 罗智泉教授 2022 年被授予第一届王选应
用数学奖
• 贺品嘉教授团队软件荣获第一届“IEEE
开源软件服务奖”
• Konstantinos Courcoubetis 教 授 论 文
荣获 INFORMS MSOM 分会“运营管理
方向最佳管理科学论文奖”
• 李海洲教授荣膺新加坡工程院院士
• 方一向教授获 2021 年数据管理国际会议
SIGMOD“突出奖”
• Arnulf Jentzen 教 授 获 2022 年“ 约 瑟
夫·特劳布基于信息复杂性研究成就奖”
• Konstantinos Courcoubetis 教授论文获
2021 国际顶级运筹与管理协会 INFORMS
MSOM 服务管理方向最佳论文奖
• 罗智泉教授荣膺中国工程院院士（外籍）
• 张 大 鹏 教 授、 丁 宏 强 教 授、 罗 智 泉 教
授、李世鹏教授（客座）、查宏远教授荣
登由全球计算机研究领域的领先门户网站
Guide2Research 公布的全球前 1000 位
计算机科学和电子领域顶级科学家榜单
• 罗智泉教授被授予 2020 世界华人数学家
联盟最佳论文奖（银奖）
• 罗智泉教授与华为技术有限公司王楠斌、
陈昕等共同完成的“5G 网络性能的建模与
优化”获得首届 CSIAM 应用数学落地成果
认证
• 张大鹏教授当选加拿大皇家科学院院士、
加拿大工程院院士。此外，张大鹏教授在
2021 年 11 月入选 2021 年度全球“高被
引科学家”名单，已连续 8 年入选该榜单
• 黄铠教授团队的科研成果《融合感知科学
云计算与 5G 物联网建立智能医疗云生态系
统》获 2020 年第十届吴文俊人工智能自然
科学奖二等奖
• 茅 剑 锋 教 授 荣 获 2020 年 Integrated
C o m m u n i c a t i o n , N a v i g a t i o n , &
Surveillance Conference 杰出论文奖
• 茅剑锋教授荣获 2020 年深圳市优秀教师
称号
• 张寅教授 2019 年当选美国工业与应用数
学学会会士（SIAM Fellow），以表彰张教
授在线性、非线性优化、遥感等领域的算法
与理论方面做出的杰出贡献
• 戴 建 岗 教 授 获 颁 2018 年 The ACM
SIGMETRICS Achievement Award，以
表彰他在排列网络稳定性及其在计算机和通
信系统应用的奠基性贡献。这是本奖项设立
16 年以来华人科学家首次获此殊荣
Research Programs
From 2020 to present, Faculty of the School
of Data Science have been granted a total
of 60 national, provincial, and municipallevel scientific research funding programs,
including 32 National Natural Science
Foundation programs with a total fund of
over ten million yuan. Among them, the
\"Innovative Exploration Program\" is the first
project of CUHK-Shenzhen.
• NSFC Innovative Exploration Program:
Online Learning and Optimization Algorithms
under Data-Scarce and Nonstationary Model
Scenarios
• 7 NSFC General Program:
1) Research on the Adversarial Phenomenon
of Deep Learning Systems based on a Unified
Mathematical Description
2) The Study on Touchless Multi-modal
Palmprint Recognition with Big Data
3) Data Driven Online Optimization for
Queueing Systems
4) Research on Several Key Issues of Kernel
Regularization System Identification
5) The Computational Model and Algorithm
for Brain-controlled Speaker Extraction Under
Multi-talker Noisy Environment
6) Kalman Filter Theory of Special Euclidean
Group and Its Application in Simultaneous
Localization and Mapping
7) Research on Asset Allocation, Timing and
Pricing Under the Framework of Behavioral
Finance
• 22 NSFC Youth Programs:
1) Investigating Asymptotic Network
Independence in Distributed Stochastic
Optimization
2) Metropolis-Hastings Reversiblizations of
Nonreversible Markov Chains
3) Post-selection Estimators and Valid
Inference for Time-series Models
4) Queues with Auto-correlated Arrivals
5) The Spectral Analysis of Large Dimensional
Non-central Fisher Matrix with Its Applications
6) Stopping Strategies of Behavioral Gamblers
with Cumulative Prospect Theory Preferences
7) Research on Key Technologies of Medical
Image Segmentation Based on Boundary
Attention Level Set
8) Data-driven Deep Omnidirectional Image
Compression for Virtual Reality
9) Large-Scale Software Reliability Engineering
via Automated Log Analysis
10) Research on Cohesive Subgraph Search
over Large Complex Heterogeneous Graphs
11) The Model, Algorithm, Theory, and
Applications of Fast Nonconvex and
Nonsmooth Tensor Recovery
12) Privacy-preserving Reinforcement Learning
via Functional Mechanisms
13) Location Auction Theory with Endogenous
Information Design in Live Shopping
14) Interpretative Logic Point Process and Its
Application in Complex Sequential Systems
15) On a Family of Stochastic Model-based
Methods and Applications in Nonsmooth
Nonconvex Optimization
16) Research on the Fusion Method of
Semantic Communication and Ad-hoc Network
for 6G Ubiquitous Perception
17) Experimental Design and Statistical
Modeling for Multiphenotypic Single-cell
Transcriptome Sequencing
18) Research on Optimization Method of Datadriven Forest Fire Emergency Management
Coordination Operation
19) Research on the User-behavior-oriented
Matching Mechanism of Online Car-hailing
Order Dispatching
20) Research on the Key Technology of
Intelligent Acquisition of Pulse Wave Signal
21) Research on Data-driven Control
Technology of Linear Time-varying System
Based on Machine Learning Kernel
Regularization Method
22) Research on Efficient Dense Subgraph
Mining Algorithm for Large-scale Directed
Graphs
•2 NSFC Research Fund for International
Scientists:
1) Higher Order-type Methods for Structured
and Stochastic Variational Inequalities
2) Stochastic Gradient Descent Provably
Overcomes All Bad Non-global Local Minima
in the Partial Training of Artificial Neural
Networks
• 4 Natural Science Foundation of
Guangdong Province General Program:
1) Research on Efficient Algorithms of Densest
Subgraph Discovery over Large-scale Directed
Graphs
2) Hierarchical Visual Content Understanding
Based on Large-scale Image-text Pretraining
3) Study on Dimensionality Expansion
Techniques for Big Data Processing
4) Subgraph Counting for Large-scale Graphs
Based on Heterogeneous Computing:
Algorithms and Applications
• Key-area Research and Development
Program of Guangdong Province: An Edge
Cloud Platform Based on Agile-customizable
Processor
• 2 Guangdong-Shenzhen Joint Fund Young
Scientists Program:
1) Research on Path Planning and Computing
Offloading in UAV assisted Mobile Edge
Network
2) Resource Optimization of Recyclable Coproducts in Sharing Platforms: A Cooperative
Game Theoretic Framework
• Guangdong-Shenzhen Joint Fund Key
Program: Finger Multimodal Feature Extraction
and Recognition
• Guangdong-Shenzhen Joint Fund Key
Program: Decision-making Problem of
Gamblers with Time-inconsistent Preference
under Prospect Theory
• Research Grants from Guangdong
Provincial Key Laboratory of Big Data
Computing:
1) Privacy and Copyright Protection of Big Data
2) Auditory Cognitive Analysis Based on Multimodel Physiological Signal
3) Collaborative Decision Making Scheme
via Multi-agent Reinforcement Learning with
Applications to Multi-airport Systems
4) Online Algorithm Design in E-commerce
and Other Applications
• 2 Key Program of Shenzhen Fundamental
Research:
1) Research on Robotic Sensing Degeneration
Mechanism, Perception and Localization
Method in Extreme Environments
2) Multi-modal and Multi-task Deep Neural
Network Design and Training
• 3 General Program of Shenzhen
Fundamental Research:
1) Research on the Methods of Anomaly
Behaviors Detection over E-commerce
Knowledge Graphs
2) Research on Some Key Problems in Kernelbased Regularized Linear System Identification
3) 6G Space-air-ground Integrate Perception
Methods Based on Mobile Edge Computing
and Multi-agents
• Shenzhen Fundamental Research Program
(Natural Science Foundation) Stability
Support Program for Higher Education
Institutions: Optimization and Applications in
Machine Learning
• Shenzhen Science and Technology
Innovation Committee Program: Study on
Computer Simultaneous Interpreting Systems
• Shenzhen Laboratory Opening Fund
Project of Shenzhen Collaborative Innovation
Program: Semi-supervised and Deep Hash
Network for Cross-modal Person-ReID
• Shenzhen Excellent Science and
Technology Innovation Talent Cultivation
Program (Start-up Program for Doctoral
Basic Research):
1) On the Design and Analysis of a Set of
Non-descent Coordinate-type Methods with
Applications to Non-smooth Optimization
Problems
2) Applications of Functional Analysis in
Differentially Private Mechanisms
• Shenzhen Excellent Science and
Technology Innovation Talent Cultivation
Program (Excellent Youth Project):
1) Online Stochastic Optimization for Complex
Queueing Systems: Algorithms and Theory
2) Research on Principles, Algorithms, and
Standardized Platforms of AI Security
3) Decentralized Stochastic Optimization in
Multi-Agent Networks
• Shenzhen Knowledge Innovation Program
[Basic Research (Free Exploration)]: Research
and Implementation of a Human-machine
Natural Language Dialogue System for Medical
and Health Services
• Shenzhen Knowledge Innovation Program
[Basic Research (Discipline Layout)]:
Research on Statistical Modeling Theory and
Distributed Optimization Methods for Large
Scale Spatial-temporal Data
44 School of Data Science
Guangdong Provincial Key
Laboratory
Guangdong Provincial Key Laboratory of Big
Data Computing (March, 2021)
Guangdong Provincial Key Laboratory of
Mathematical Foundations for Artificial
Intelligence
Shenzhen Municipal Key
Laboratory
Shenzhen Key Laboratory of Pattern Analysis
and Perceptual Computing (Piloting phase)
School-enterprise Joint
Laboratory
CUHK(SZ)-Linklogis Joint Laboratory of
CV and AI
Academic Papers
A contingent of top-notch research teams led
by SDS faculty has published more than 328+
high-quality professional papers in many wellknown international conferences and top journals
since the establishment of SDS in 2020.
Books
• Prof. Dapeng Zhang David - Information
Fusion: Machine Learning Methods, with
Jinxing Li and Bob Zhang, 2022, Springer
Singapore and Advanced Fingerprint
Recognition: From 3D Shape to Ridge Detail,
with Feng Liu, Qijun Zhao, 2020, Springer
• Prof. Jiangang Dai Jim - Processing
Networks Fluid Models and Stability, with J.
Michael Harrison, 2020, Cambridge University
Press
• Prof. Tianshi Chen - Regularized System
Identification: Learning Dynamic Models from
Data, with Gianluigi Pillonetto, Alessandro
Chiuso, Giuseppe De Nicolao, Lennart Ljung,
2021, Springer
• Prof. Jianhua Huang - A New Model of
Capital Asset Prices: Theory and Evidence,
with James W. Kolari, Wei Liu, 2021, Palgrave
Macmillan
• Prof. Yixiang Fang - Cohesive Subgraph
Search Over Large Heterogeneous Information
Networks, with Kai Wang, Xuemin Lin, and
Wenjie Zhang, 2022, Springer
• Prof. Zizhuo Wang - The Elements of Joint
Learning and Optimization in Operations
Management, with Qi Chen, He Wang, 2022,
Springer
Awards / Scientific Honors
(excerpt)
• Prof. Yin Zhang from the School of Data
Science, CUHK-Shenzhen, won Paul Y.
Tseng Memorial Lectureship in Continuous
Optimization
• Prof. Haizhou Li's team of the School of
Data Science won the Second Place in 2022
VoxCeleb Speaker Recognition Challenge
(VoxSRC)
• Prof. Benyou Wang's Paper from the School
of Data Science, CUHK-Shenzhen, won the
NLPCC 2022 Best Paper Award
• Prof. Tianshi Chen from the School of Data
Science, CUHK-Shenzhen was awarded the
2022 Accomplished Educator of Shenzhen
• 4 Professors including Xiaoqiang Cai, Kai
Hwang, Haizhou Li and David Zhang, were
elected as AAIA Fellows
• Prof. Jianhua Huang won the 2022
INFORMS Impact Prize
• Prof. Haizhou Li's Team won the Oriental
COCOSDA 2022 Best Paper Award
• 17 SDS Professors including Tianshi Chen,
Chris Ding, Yixiang Fang, Guillermo Gallego,
Jianhua Huang, Kai Hwang, Arnulf Jentzen,
Haizhou Li, Zhiquan Luo, Yiming Miao, Ruoyu
Sun, Baoyuan Wu, Zhizheng Wu, Ming Yan,
Hongyuan Zha, David Zhang, Yin Zhang, listed
the World's Top 2% Scientists
• Prof. Zhiquan Luo Tom was awarded the
First CSIAM Wangxuan Prize (2022)
• Prof. Pinjia He and his team won the first
IEEE Open Software Services Award
• Prof. Konstantinos Courcoubetis was
awarded Management Science Best Paper
Award in Operations Management from
INFORM MSOM
• Prof. Haizhou Li was inducted as the
Academy of Engineering Singapore Fellow
• Prof. Yixiang Fang received the certificate of
2021ACM SIGMOD Research Highlight Award
Prof. Arnulf Jentzen received the Joseph F.
Traub Prize for Achievement in InformationBased Complexity
• Prof. Konstantinos Courcoubetis was
awarded 2021 MSOM Service Management
Special Interest Group Best Paper Award
• Prof. Zhiquan Luo Tom was appointed as a
Foreign Member of the Chinese Academy of
Engineering (CAE)
• Prof. Dapeng Zhang David, Prof. Hongqiang
Ding Chris, Prof. Zhiquan Luo Tom, Prof.
Shipeng Li (Adjunct), Prof. Hongyuan Zha were
elected as Top 1000 Scientists in Computer
Science and Electronics by Guide2Research
• Prof. Zhiquan Luo Tom was awarded 2020
ICCM Best Paper Award by International
Consortium of Chinese Mathematicians
• Prof. Zhiquan Luo Tom, and Nanbin Wang,
Xin Chen (from Huawei Technologies Co., Ltd.)
obtained the first CSIAM Applied Mathematics
Landing Achievement Certification with their
program \"Modeling and Optimization of 5G
Network Performance\"
• In September 2020, Prof. Dapeng Zhang
David was elected a New Fellow of the Royal
Society of Canada. In November 2020, he was
announced in the “Highly Cited Researchers
2020” list and has been on the list for seven
consecutive years
• Prof. Kai Hwang and his research team won
the second prize of the 10th WU WEN JUN AI
SCIENCE & TECHNOLOGY AWARD in 2020
with their achievement “Cognitive Cloud and
5G IoT for Public Healthcare Ecosystem”
• Prof. Jianfeng Mao was awarded 2020
Integrated Communication, Navigation &
Surveillance Conference Outstanding Paper
Award
• Prof. Jianfeng Mao won 2020 Shenzhen
Excellent Teacher Award
• Prof. Yin Zhang was elected a SIAM Fellow
of the Society of Industrial and Applied
Mathematics (SIAM) in 2019, in recognition
of his outstanding contributions to algorithms
and theories in linear, nonlinear optimization,
remote sensing and other fields
• The 2018 ACM SIGMETRICS Achievement
Award is given to Prof. Jiangang Dai Jim for
his fundamental contributions to the analysis
of the stability of queueing network with
applications to computer and communication
systems
Academic Achievements
sds.cuhk.edu.cn 45
46 School of Data Science
STUDENT
ACHIEVEMENTS
学生成就
董婧（2021 级数据科学博士生）与李可、
李 帅、 王 趵 翔 合 著 论 文《Combinatorial
Bandits under Strategic Manipulations》
被 2022 年国际互联网检索与数据挖掘会议
收录。
https://doi.org/10.1145/3488560.3498413
Jing Dong (first author, M.Phil- Ph.D.
Programme in Data Science, 2021 Cohort), Ke
Li (co-author, undergraduate Computer Science
and Engineering student, 2018 Cohort), Shuai
Li, Boxiang Wang. Combinatorial Bandits
under Strategic Manipulations, WSDM: The
Fifteenth International Conference on Web
Search and Data Mining 2022.
https://doi.org/10.1145/3488560.3498413
董婧（合著作者，2021 级数据科学博士生）
与 Kun Wang、王趵翔、Shuai Li、Shuo
Shao 合 著 论 文 被《Cascading Bandits
under Differential Privacy》2022 年
IEEE 声学、语音与信号处理国际会议收录。
Jing Dong (co-author, M.Phil.-Ph.
D. Programme in Data Science, 2021
Cohort), Kun Wang, Baoxiang Wang, Shuai
Li, Shuo Shao. Cascading Bandits under
Differential Privacy, IEEE International
Conference on Acoustics, Speech, and Signal
Processing (ICASSP) 2022.
https://ieeexplore.ieee.org/stamp/stamp.
jsp?arnumber=9746966
李子牛（第一作者，2020 级数据科学博士
生）、张雨舜（合著作者，2019 级数据科
学博士生）与李英儒、张潼、罗智泉合著论
文《HyperDQN: 一种适用于深度强化学习
的随机探索方法》被 2022 年国际表征学习
大会收录。
Ziniu Li (first author, M.Phil.-Ph.D. Programme
in Data Science, 2020 Cohort), Yushun Zhang
(co-author, M.Phil.-Ph.D. Programme in Data
Science, 2019 Cohort), Yingru Li, Tong Zhang,
Zhi-Quan Luo. HyperDQN: A Randmoized
Exploration Method for Deep Reinforcement
Learning, International Conference on Learning
Representations (ICLR) 2022.
https://openreview.net/pdf?id=X0nrKAXu7g李子牛（第一作者，2020 级数据科学博士
生）、许天、俞扬、罗智泉合著论文《重新
思考 ValueDice: 它真的提升性能了吗 ?》
被 2022 年国际表征学习大会收录。
Ziniu Li (first author, M.Phil.-Ph.D. Programme
in Data Science, 2020 Cohort), Tian Xu, Yang
Yu, Zhi-Quan Luo. Rethinking ValueDice: Does
it Really Improve Performance? International
Conference on Learning Representations (ICLR)
2022.
https://arxiv.org/abs/2202.02468
Dmitry Rybin（ 通 讯 作 者，2021 级 数 据
科 学 博 士 生）、Sergei Kudria（ 合 著 作
者，2021 级 数 据 科 学 博 士 生） 与 Lgor
Vasyliev、Ren Jie、Zhang Dong 合
著 论 文《Multiple project scheduling
for a network roll-out problem: MIP
formulation and heuristic》被《Springer
Verlag, Lecture Notes in Computer
Science》期刊收录。
Dmitry Rybin (corresponding author, M.Phil.-
Ph.D. Programme in Data Science, 2021
Cohort), Sergei Kudria (co-author, M.Phil.-Ph.
D. Programme in Data Science, 2021 Cohort),
Lgor Vasyliev, Ren Jie, Zhang Dong. Multiple
project scheduling for a network roll-out
problem: MIP formulation and heuristic,
Springer Verlag, Lecture Notes in Computer
Science.
余博西（第一作者，2021 级数据科学博士
生）、与钟智庆，秦欣然，姚嘉奕，王远程，
贺品嘉合著论文《图像描述系统的自动化测
试方法》被 2022 年计算机协会大会收录。
Boxi Yu (1st author, M.Phil.-Ph.D. Programme
in Data Science, 2021 Cohort), Zhiqing
Zhong, Xinran Qin, Jiayi Yao, Yuancheng
Wang, Pinjia He. Automated Testing of Image
Captioning Systems, Association for Computing
Machinery (ACM) 2022.
https://arxiv.org/abs/2206.06550
欧阳屹东（第四作者，2021 级数据科学博
士生）、与王晋东、Cuiling Lan、Chang
Liu、Tao Qin、Wang Lu、Wenjun
Zeng、Philip S. Yu 合著论文《泛化到未
知领域：领域泛化的综述》被 IEEE 知识与
数据工程汇刊收录。
Yidong Ouyang (4th author, M.Phil.-Ph.D.
Programme in Data Science, 2021 Cohort),
Jindong Wang, Cuiling Lan, Chang Liu, Tao
Qin, Wang Lu, Wenjun Zeng, Philip S. Yu.
Generalizing to unseen domains: A survey
on domain generalization, Transactions on
Knowledge and Data Engineering (IEEE TKDE).
https://ieeexplore.ieee.org/document/9782500
张雨舜（第一作者，2019 级数据科学博
士生）、陈淙靓与罗智泉合著论文《Does
Adam Converge and When》被 2022 年
国际表征学习大会博客赛道（ICLR-Blog
Track）收录。
Yushun Zhang (first author, M.Phil.-Ph.D.
Programme in Data Science, 2019 Cohort),
Congliang Chen, Zhi-Quan Luo. Does Adam
Converge and When? International Conference
on Learning Representations, Blog Track (ICLRBlog Track) 2022.
https://iclr-blog-track.github.io/2022/03/25/
does-adam/
王利戎（第三作者，2021 级数据科学硕士
生）与黄坚、王伟合著论文《深度强化学习
在交通信号控制优化方面的应用》2021 年
被 IEEE HPCC 收录。
Lirong Wang (3rd author, M.Sc. in Data
Science, 2021 Cohort), Jian Huang, Wei
Wang. Application of Deep Reinforcement
Learning in Optimization of Traffic Signal
Control (IEEE) 2021.
https://ieeexplore.ieee.org/document/9781001
论文发表（部分列举）Papers (Non-exhaustive List)
Student Achievements
宋若一（第二作者，2021 级数据科学硕士
生）与刘博、向玥佳、杜俊博、阮威健、
胡金辉合著论文《基于多模态对比学习的
自监督实体对齐》2022 年被 IEEE/CAA
Journal of Automatica Sinica 收录。
Ruoyi Song (2nd author, M.Sc. in Data
Science, 2021 Cohort), Bo Liu, Yuejia
Xiang, Junbo Du, Weijian Ruan, Jinhui Hu.
Self supervised entity alignment based on
multimodal contrastive learning (IEEE/CAA)
2022. (In Press, Accepted in June)
https://www.ieee-jas.net/en/article/doi/10.1109/
JAS.2022.105962
李琛良（第二作者，2021 级数据科学硕士
生） 与 曾 思 亮、Alfredo Garicia、 洪 明 毅
合 著 论 文《Maximum-Likelihood Inverse
Reinforcement Learning with Finite-Time
Guarantees 》2022 年 被 ICML workshop
DARL 收录。
Chenliang Li (2nd author, M.Sc. in Data
Science, 2021 Cohort), Siliang Zeng, Alfredo
Garicia, Mingyi Hong. Maximum-Likelihood
Inverse Reinforcement Learning with FiniteTime Guarantees (ICML) 2022.
https://openreview.net/forum?id=FfELl5h3N
ec&referrer=%5Bthe%20profile%20of%20
Chenliang%20Li%5D(%2Fprofile%3Fid%3D~Ch
enliang_Li3)
张雨舜（2019 级数据科学博士生）与张佳
伟、洪明毅、孙若愚、罗智泉合著论文《When
Expressivity Meets Trainability: Fewer
than n Neurons Can Work》被 2021 年
神经信息处理系统大会收录。
https://nips.cc/Conferences/2021/
ScheduleMultitrack?event=33025
Yushun Zhang (first author, M.Phil- Ph.D.
Programme in Data Science, 2019 Cohort),
Jiawei Zhang (first author), Mingyi Hong,
Ruoyu Sun (co-author), Zhi-Quan Luo. When
Expressivity Meets Trainability: Fewer than n
Neurons Can Work, NeurIPS 2021.
https://proceedings.neurips.cc/paper/2021/file/4c
7a167bb329bd92580a99ce422d6fa6-Paper.pdf
江昊东 ( 合著作者 ，2021 级数据科学博士
生 ) 与 Xinghan Li、Xingyu Chen、He
Kong、吴均峰合著论文《Closed-Form
Error Propagation on SEn(3) Group
for Invariant EKF With Applications
to VINS》被《IEEE Robotics and
Automation Letters》期刊收录。
Haodong Jiang (co-author, Ph.D. Programme
in Data Science, 2021), Xinghan Li, Xingyu
Chen, He Kong, Junfeng Wu. Closed-Form
Error Propagation on SEn(3) Group for
Invariant EKF With Applications to VINS, IEEE
Robotics and Automation Letters, 2022.
https://ieeexplore.ieee.org/abstract/
document/9844243/
张雪遥（第一作者，2022 级数据科学博士
生）与张金超、邱耀、王力、周杰等合著论
文《基于和声感知学习的流行音乐结构性增
强方法》被 2022 年国际多媒体会议收录。
Xueyao Zhang (first author, Ph.D. Programme
in Data Science, 2022 Cohort), Jinchao
Zhang, Yao Qiu, Li Wang, Jie Zhou. StructureEnhanced Pop Music Generation via HarmonyAware Learning, Proceedings of the 30th ACM
International Conference on Multimedia (ACM
MM 2022).
https://arxiv.org/pdf/2109.06441.pdf
黄琨（第一作者，2020 级数据科学博士生）
与濮实合著论文《关于提升分布式随机梯度
算法的暂态时间》被《IEEE Transactions
on Automatic Control》期刊收录。
Kun Huang (first author, Ph.D. Programme
in Data Science, 2020 Cohort) and Shi
Pu. Improving the Transient Times for
Distributed Stochastic Gradient Methods, IEEE
Transactions on Automatic Control.
https://ieeexplore.ieee.org/abstract/
document/9865230
张雨舜（第一作者，2019级数据科学博士生）
与陈淙靓、石乃琛、孙若愚、罗智泉合著论
文《Adam Can Converge Without Any
Modification on Update Rules》被 2022
年神经信息处理系统大会 (NeurIPS 2022)
会议收录。
Yushun Zhang (first author, Ph.D. Programme in
Data Science, 2019 Cohort), Congliang Chen,
Naichen Shi, Ruoyu Sun, Zhi-Quan Luo. Adam
Can Converge Without Any Modification on
Update Rules, Conference on Neural Information
Processing Systems (NeurIPS), 2022.
https://arxiv.org/abs/2208.09632
郑润锴（第一作者，2021 级数据科学硕士
研究生）与唐荣骏、李建泽、刘李合著论文
《基于通道的利普希茨性质进行无需数据的
后门移除》被 2022 年欧洲计算机视觉国际
会议收录。
Runkai Zheng (first author, M.Sc. in Data
Science Programme, 2021 Cohort), Rongjun
Tang, Jianze Li, Li Liu. Data-free Backdoor
Removal based on Channel Lipschitzness,
European Conference on Computer Vision
(ECCV) 2022.
https://www.ecva.net/papers/eccv_2022/papers_
ECCV/papers/136650171.pdf
陈泓瑞（合著作者，2022 级计算机科学
博士生）与吴保元 、张明达（合著作者，
2022 级数据科学博士生）、朱梓豪（合著
作者，2021 级数据科学博士生）、魏少魁（合
著作者，2020 级数据科学博士生）、袁丹
妮（合著作者，2022 级计算机科学博士生）、
沈超、查宏远合著论文《BackdoorBench：
一个全面的后门学习基准》被 2022 年神经
信息处理系统大会收录。
Hongrui Chen (co-author, Ph.D. Programme
in Computer Science, 2022 Cohort), Baoyuan
Wu, Mingda Zhang (co-author, Ph.D.
Programme in Data Science, 2022 Cohort),
Zihao Zhu (co-author, Ph.D. Programme in
Data Science, 2021 Cohort), Shaokui Wei (coauthor, Ph.D. Programme in Data Science,
2020 Cohort), Danni Yuan (co-author,
Ph.D. Programme in Computer Science,
2022 Cohort), Chao Shen, Hongyuan Zha.
BackdoorBench: A Comprehensive Benchmark
of Backdoor Learning, Thirty-sixth Conference
on Neural Information Processing Systems
Datasets and Benchmarks Track.
https://openreview.net/forum?id=31_U7n18gM7.
许高远（第一作者，2021 级数据科学硕
士 研 究 生） 与 石 健、 姜 文 倩、 吴 辰 晔、
王 丹、 韩 竹 合 著 论 文《A Two-stage
Emission Mismatch Penalty Game to
Facilitate Carbon and Electricity Market
Interaction》被 2022 年 IEEE 能源互联网
与能源系统集成国际会议收录。
Gaoyuan Xu (first author, M.Sc. in Data
Science Programme, 2021 Cohort), Jian Shi,
Wenqian Jiang, Chenye Wu, Dan Wang, Zhu
Han, A Two-stage Emission Mismatch Penalty
Game to Facilitate Carbon and Electricity
Market Interaction, IEEE Conference on Energy
Internet and Energy System Integration (IEEE
EI2) 2022.
https://attend.ieee.org/ei2-2022/programs/z
sds.cuhk.edu.cn 47
陈建文（2020 级数据科学与大数据技术专
业本科生）、金德容（2020 级计算机科学
与技术本科生）获得 3 项赛事奖项：
• 2021 年 ICPC 国际大学生程序设计竞赛
亚洲区域赛上海站铜奖
• 2022 年 ICPC 国际大学生程序设计竞赛
亚洲区域赛昆明站银奖
• 2022 年 广 东 省 大 学 生 程 序 设 计 竞 赛
（CCPC 广东省赛）银奖
Jianwen Chen (Undergraduate in Data Science
and Big Data Technology, 2020 Cohort) and
Derong Jin (Undergraduate in Computer
Science and Engineering, 2020 Cohort) won 3
prizes in competition:
• Bronze medal in the 2021 International
Collegiate Programming Contest Asia Regional
Contest Shanghai Site
• Silver medal in the 2022 International
Collegiate Programming Contest Asia Regional
Contest Kunming Site
• Silver medal in the 2022 Guangdong
Collegiate Programming Contest
郭青硕（2021 级数据科学学院本科生）、
侯天赐（2021 级数据科学学院本科生）、
曲恒毅（2020 级计算机科学与技术本科生）
获得 4 项赛事奖项：
• 2021 年 ICPC 国际大学生程序设计竞赛
亚洲区域赛沈阳站银奖
• 2021 年 CCPC 中国大学生程序设计竞赛
哈尔滨站金奖
• 2021 年 CCPC 中国大学生程序设计竞赛
广州站银奖
• 2022 年广东省大学生程序设计大赛金奖
Qingshuo Guo (Undergraduate in Common
Plan of BEng, 2021 Cohort), Tianci Hou
(Undergraduate in Common Plan of BEng,
2021 Cohort), Hengyi Qu (Undergraduate in
Computer Science and Engineering, 2020
Cohort) won 4 prizes in competition:
• Silver medal in the 2021 International
Collegiate Programming Contest Asia Regional
Contest Shenyang Site
• Silver medal in the 2021 Chinese College
Student Programming Competition Haerbin Site
• Silver medal in the 2021 Chinese College
Student Programming Competition Guangzhou Site
• Gold medal in the 2022 Guangdong
Collegiate Programming Contest
蒋一歌（2021 级数据科学学院本科生）、
夏禹扬（2021 级数据科学学院本科生）、
赵子逸（2021 级数据科学学院本科生）获
得 5 项赛事奖项：
• 2021 年国际大学生程序设计竞赛（ICPC）
亚洲区域赛济南站银奖
• 2021 年国际大学生程序设计竞赛（ICPC）
亚洲区域赛上海站银奖
• 2021 年 中 国 大 学 生 程 序 设 计 竞 赛
（CCPC）威海站银奖
• 2022 年广东省大学生程序设计大赛金奖
• 第 46 届国际大学生程序设计竞赛亚洲区
决赛铜牌
Yige Jiang (Undergraduate in Common
Plan of BEng, 2021 Cohort), Yuyang Xia
(Undergraduate in Common Plan of BEng,
2021 Cohort), Ziyi Zhao (Undergraduate in
Common Plan of BEng, 2021 Cohort) won 5
prizes in competition:
• Silver medal in the 2021 International
Collegiate Programming Contest Asia Regional
Contest Ji’nan Site
• Silver medal in the 2021 International
Collegiate Programming Contest Asia Regional
Contest Shanghai Site
• Silver medal in the 2021 Chinese College
Student Programming Competition Weihai Site
• Gold medal in the 2022 Guangdong
Collegiate Programming Contest
• Bronze medal in the Asian final of the 46th
International Collegiate Programming Contest
蒋紫涵（2019 级统计学本科生）获得 1 项
赛事奖项：
• 2021 全球开放数据应用创新大赛创意赛
道数字文旅分赛道二等奖
Zihan Jiang (Undergraduate in Statistic, 2019
Cohort) won 1 prize in competition:
• The second prize of the creative track digital
cultural tourism sub-track in the 2021 global
open data application innovation competition
忙秋阳（2021 级数据科学学院本科生）、徐
源（2021 级数据科学学院本科生）获得 6
项赛事奖项：
• 2021 年 ICPC 国际大学生程序设计竞赛
亚洲区域赛沈阳站金奖
• 2021 年 ICPC 国际大学生程序设计竞赛
亚洲区域赛南京站金奖
• 2021 年 CCPC 中国大学生程序设计竞赛
桂林站金奖
• 2021 年 CCPC 中国大学生程序设计竞赛
广州站金奖
• 第 46 届国际大学生程序设计竞赛亚洲区
决赛金牌
• 第 7 届中国大学生程序设计竞赛总决赛银牌
Qiuyang Mang, Yuan Xu (Undergraduate in
Common Plan of BEng, 2021 Cohort) won 6
prizes in competition:
• Gold medal in the 2021 International
Collegiate Programming Contest Asia Regional
Contest Shenyang Site
• Gold medal in the 2021 International
Collegiate Programming Contest Asia Regional
Contest Nanjing Site
• Gold medal in the 2021 Chinese College
Student Programming Competition Guilin Site
• Gold medal in the 2021 Chinese College
Student Programming Competition Guangzhou Site
• Gold medal in the Asian final of the 46th
International Collegiate Programming Contest
• Silver medal in the 7th China Collegiate
Programming Contest
杨宇昊（2021 级数据科学硕士生）获得 1
项赛事奖项：
• 2021 第五届“神威杯”国产 CPU 并行
应用挑战赛三等奖
Yuhao Yang (M.Sc. in Data Science, 2021
Cohort) won 1 prize in competition:
•The third prize of the 5th China Parallel
Application Challenge On Domestic CPU
胡湘（2021 级数据科学硕士生）获得 1 项
赛事奖项：
• 2021 香港中文大学（深圳）编程竞赛进
阶组二等奖
Xiang Hu (M.Sc. in Data Science, 2021
Cohort) won 1 prize in competition:
•The second prize of the 2021 The
Chinese University of Hong Kong, Shenzhen
Programming Competition Advanced Group.
奖项荣誉（部分）Awards and Hornors (Non-exhaustive List)
48 School of Data Science
