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Prof. Reynold C.K. Cheng
鄭振剛教授

Professor,  Department of Computer Science, HKU

Distinguished Member, ACM

 

Associate Dean of Engineering (Student Enrichment)

Program Director, Data Science and Engineering

Deputy Director, Law and Technology Centre, HKU

Address: University of Hong Kong, CB303, Chow Yei Ching Building, Pokfulam Road, Hong Kong

(+852) 2219 4778

Reynold Cheng is a Professor of the Department of Computer Science in the University of Hong Kong (HKU). His research interests are in data science, big graph analytics and uncertain data management. He was an Assistant Professor in the Department of Computing of the Hong Kong Polytechnic University (HKPU) from 2005 to 2008. He received his BEng (Computer Engineering) in 1998, and MPhil (Computer Science and Information Systems) in 2000 from HKU. He then obtained his MSc and PhD degrees from Department of Computer Science of Purdue University in 2003 and 2005.

 

Prof. Cheng received the ACM Distinguished Membership Award and the HKU Outstanding Research Student Supervisor Award in 2023. He was listed as the World’s Top 2% Scientists by Stanford University in 2022, and the 2023 AI 2000 Most Influential Scholar in Database. He received the SIGMOD Research Highlights Reward 2020, HKICT Awards 2021, and HKU Knowledge Exchange Award (Engineering) 2021. He was granted an Outstanding Young Researcher Award 2011-12 by HKU. He received the Universitas 21 Fellowship in 2011, and two Performance Awards from HKPU Computing in 2006 and 2007. He is an academic advisor to the College of Professional and Continuing Education of HKPU. He is a member of IEEEACMACM SIGMOD, and UPE. He was a PC co-chair of IEEE ICDE 2021, and has been serving on the program committees and review panels for leading database conferences and journals like SIGMOD, VLDB, ICDE, KDD, IJCAI, AAAI, and TODS. He is on the editorial board of IS and DAPD, and was a former editorial board member of TKDE.

Our lab has a few openings for Postdocs and Ph.D this year. We are looking for talents with research interest in data science (including databases, data mining, NLP, machine learning, AI).  If you are interested, please feel free to email your CV, transcripts, and email to me. Here is the official website for Ph.D and MPhil student recruitment.

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Recent Publications

Finding Locally Densest Subgraphs: A Convex-Programming Approach

Proc. VLDB Endow. 15(2022). Also in the Very Large Databases Conf. (VLDB 2022), Sydney, Australia, Sep 2022

C. Ma*, R. Cheng, L. Lakshmanan, and X. Han

DeepTEA: Effective and Efficient Online Time-dependent Trajectory Outlier Detection

Proc. VLDB Endow. 15(2022). Also in the Very Large Databases Conf. (VLDB 2022), Sydney, Australia, Sep 2022

X. Han*, R. Cheng, T. Grubenmann, and C. Ma*

A Convex-Programming Approach for Efficient Directed Densest Subgraph Discovery

ACM SIGMOD Conference 2022, June 2022, Philadelphia, PA, USA

C. Ma*, Y. Fang, R. Cheng, L. Lakshmanan, and X. Han

Recent Projects

HINCare: A Heterogeneous Information Network for Elderly-Care Recommendation
Jockey Club SMART Family-Link Project (JCSFL)
 
Jockey Club Holistic Support Project for Elderly Mental Wellness (Second Phase)
Jockey Club Golden Age Journey Project
 
Application System Development for the Aberdeen Kai-Fong Welfare Association Social Service Centre (AKA Social Service)
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