Prof. Li CHEN at HKBU

Recent Publications

MemRec: Collaborative Memory-Augmented Agentic Recommender System. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL'26), July 2-7, 2026.

The Double-Edged Sword of Knowledge Transfer: Diagnosing and Curing Fairness Pathologies in Cross-Domain Recommendation. Proceedings of the ACM Web Conference (WWW'26), June 29-July 3, 2026.

A Cross-Domain Study on the User Experience of ChatGPT-based Recommendations. International Journal of Human-Computer Studies (IJHCS), 2026.

Causality-Inspired Fair Representation Learning for Multimodal Recommendation. ACM Transactions on Information Systems (TOIS), 2025.

DAR: Dimension-Adaptive Recommendation with Multi-Granular Noise Control. In Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'25), July 13-18, 2025.

From Pairwise to Ranking: Climbing the Ladder to Ideal Collaborative Filtering with Pseudo-Ranking. In Proceedings of the 39th Annual AAAI Conference on Artificial Intelligence (AAAI’25), February 25 - March 4, 2025.

Prof. Li CHEN (陳黎)

Associate Head (Research) and Professor, Department of Computer Science

Professor (Affiliate), Academy of Wellness and Human Development

Hong Kong Baptist University, China

Education:

PhD in Computer Science (Nominee for Best PhD Thesis Award), Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland
Master in Computer Software and Theory, Peking University (北京大學), China
Bachelor in Computer Science, Peking University (北京大學), China

Google scholar profile: h-index 53, i10-index 125, citations 13,124 (till April 2026)

Short bio:

Professor Chen’s research focus has mainly been on human-centered AI, recommender systems, conversational UI, and explainable UI, with applications covering various domains especially mental well-being and digital media in recent years. She has authored and co-authored over 160 publications, most of which appear in high-impact journals (such as IJHCS, CSCW, TOCHI, TOIS, UMUAI, TIST, TIIS, KNOSYS, Behavior & Information Technology, AI Magazine, and IEEE Intelligent Systems), and key conferences in the areas of data mining (SIGKDD, WSDM, SDM), artificial intelligence (IJCAI, AAAI), information retrieval (SIGIR), recommender systems (RecSys), user modeling (UMAP), and intelligent user interfaces (CHI, IUI, Interact).

Her co-authored papers have received several awards, including the RecSys’24 Best Student Paper Award, CHI’22 Honourable Mention Award, UMAP’20 Best Student Paper Award, UMUAI 2018 Best Paper Award, and UMAP’15 Best Student Paper Award. She received the President’s Award for Outstanding Performance in Teaching (Individual) 2024/25 and the President’s Award for Outstanding Performance in Research Supervision 2022/23. She has been included in the list of the world’s top 2% most-cited scientists by Stanford University since 2021, and the list of the Best Computer Science Scientists 2025/2026 by Research.com. She is now an ACM senior member, founding editor-in-chief of ACM Transactions on Recommender Systems (TORS), steering committee member of ACM Conference on Recommender Systems (RecSys), editorial board member of User Modeling and User-Adapted Interaction Journal (UMUAI), and associate editor of ACM Transactions on Interactive Intelligent Systems (TiiS). She has also served as the program co-chair of IUI’26, the general co-chair of ACM RecSys’23, the program co-chair of ACM RecSys’20, and the program co-chair of ACM UMAP’18.

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