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Professor Reynold Cheng
Professor
Department of Computer Science
ckcheng@cs.hku.hk (852) 2219 4778
CB303, Department of Computer Science, HKU 
Key expertise
Databases and Data Science
About me

Prof. 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 the 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 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 IEEE, ACM, ACM 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.

Selected Publications
  • Chenhao Ma, Reynold Cheng, Laks V. S. Lakshmanan, and Xiaolin Han. “Finding locally densest subgraphs: a convex programming approach.” Proc. VLDB Endow. 15, 11 (July 2022), 2719–2732. https://doi.org/10.14778/3551793.3551826, (2022).
  • Xiaolin Han, Reynold Cheng, Chenhao Ma, and Tobias Grubenmann. “DeepTEA: effective and efficient online time-dependent trajectory outlier detection.” Proc. VLDB Endow. 15, 7 (March 2022), 1493–1505. https://doi.org/10.14778/3523210.3523225, (2022).
  • Chenhao Ma, Yixiang Fang, Reynold Cheng, Laks V. S. Lakshmanan, and Xiaolin Han. “A Convex-Programming Approach for Efficient Directed Densest Subgraph Discovery.” In Proceedings of the 2022 International Conference on Management of Data (SIGMOD ’22). Association for Computing Machinery, New York, NY, USA, 845–859. https://doi.org/10.1145/3514221.3517837, (2022).
  • Xiaolin Han, Reynold Cheng, Tobias Grubenmann, Silviu Maniu, Chenhao Ma, and Xiaodong Li. “Leveraging Contextual Graphs for Stochastic Weight Completion in Sparse Road Networks.” SIAM International Conference on Data Mining (SDM 2022), April 2022. https://epubs.siam.org/doi/pdf/10.1137/1.9781611977172.8, (2022).
  • Chenhao Ma, Yixiang Fang, Reynold Cheng, Laks V. S. Lakshmanan, Wenjie Zhang, and Xuemin Lin. “On Directed Densest Subgraph Discovery.” ACM Trans. Database Syst. 46, 4, Article 13 (December 2021), 45 pages. https://doi.org/10.1145/3483940, (2021).
  • Xiaodong Li, Reynold Cheng, Kevin Chen-Chuan Chang, Caihua Shan, Chenhao Ma, and Hongtai Cao. “On analyzing graphs with motif-paths.” Proc. VLDB Endow. 14, 6 (February 2021), 1111–1123. https://doi.org/10.14778/3447689.3447714, (2021).
  • Tsz Nam Chan, Zhe Li, Leong Hou U, Jianliang Xu, and Reynold Cheng. “Fast augmentation algorithms for network kernel density visualization.” Proc. VLDB Endow. 14, 9 (May 2021), 1503–1516. https://doi.org/10.14778/3461535.3461540, (2021).
  • Dan He, Sibo Wang, Xiaofang Zhou, and Reynold Cheng. “GLAD: A Grid and Labeling Framework with Scheduling for Conflict-Aware kkNN Queries.” IEEE Transactions on Knowledge and Data Engineering, vol. 33, no. 4, pp. 1554-1566, 1 April 2021, DOI: 10.1109/TKDE.2019.2942585, (2021).
  • Chenhao Ma, Yixiang Fang, Reynold Cheng, Laks V. S. Lakshmanan, Wenjie Zhang, and Xuemin Lin. “On Directed Densest Subgraph Discovery.” ACM Trans. Database Syst. 46, 4, Article 13 (December 2021), 45 pages. https://doi.org/10.1145/3483940, (2021).
  • Zichen Zhu, Tsz Nam Chan, Reynold Cheng, Loc Do, Zhipeng Huang, and Haoci Zhang. “Effective and Efficient Discovery of Top-k Meta Paths in Heterogeneous Information Networks.” In the Transactions on Knowledge and Data Engineering (IEEE TKDE) (Early access), Nov 2020, DOI: 10.1109/TKDE.2020.3037218, (2021).
Research Interests

Databases science, graph databases, uncertain data management

Award
Funding

[External grants] 

  1. SMART Family-Link Phase 2 (The Hong Kong Jockey Club Charities Trust (HKJC), Oct 2022- Sep 2025). [PI]
  2. Using Knowledge Graphs for Long-Tail Keyword Query Recommendation in Video Search (HKU-TCL Joint Research Centre for Artificial Intelligence, Ref: 200009430, Nov 2020-Aug 2023). [PI]
  3. A real-time monitoring and warning system for COVID-19 and influenza infection in building environment (Collaborative Research Funding (CRF) 2021/22 and Second Round One-off CRF COVID and NID Research Exercises, Ref: C7104-21G). [Co-PI]
  4. HINCare: A Heterogeneous Information Network for Elderly-Care Helper Recommendation (Innovation and Technology Fund (ITF) – Midstream Research Programme for Universities (MRP), Ref: MRP/029/18, 2019-2021). [PI]
  5. User-driven Asset-centric Ecosystem for Democratizing Data Science and AI, France/Hong Kong Joint Research Scheme – Travel Grants, Ref: F-HKU702/20, 1/2/2021-31/1/2023. [PI (project partner: Sihem Amer-Yahia)]

Total: 22 projects (amounting to ~HK88 million)