Prof. CHEN, Li
Prof. CHEN, Li

陳黎教授
BSc, MSc, PhD
Associate Head (Research) and Professor, Department of Computer Science
Professor (Affiliate), Department of Social Work
https://www.comp.hkbu.edu.hk/~lichen/
 

About

Professor Chen Li is currently a Professor and Associate Head (Research) in the Department of Computer Science at Hong Kong Baptist University (HKBU). She obtained her PhD degree in Computer Science from the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland, and her Bachelor's and Master's degrees from Peking University, China. Her recent research focus has mainly been on conversational and explainable AI, with applications covering various domains including entertainment, digital media, education, e-commerce, and psychological well-being. She has authored and co-authored over 120 publications, with 8,900 citations so far (H-index 46). Her co-authored papers have received several awards, such as the 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 Research Supervision 2022/23, and has been included in the list of the world’s top 2% most-cited scientists by Stanford University since 2021. She is now an ACM senior member, co-editor-in-chief of ACM Transactions on Recommender Systems (TORS), executive 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 also served as 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.


Research Interests

  • Conversational AI
  • Explainable AI
  • Recommender Systems
  • Human-Computer Interaction

Selected Publications

  • Yucheng Jin, Wanling Cai, Li Chen, Yuwan Dai, and Tonglin Jiang. Understanding Disclosure and Support in Social Music Communities for Youth Mental Health. In Proceedings of the ACM on Human-Computer Interaction (CSCW’23), vol. 7, Article 153, 2023.
  • Lei Li, Yongfeng Zhang, and Li Chen. Personalized Prompt Learning for Explainable Recommendation. ACM Transactions on Information Systems (TOIS), vol. 41(4), 2023. 
  • Ningxia Wang and Li Chen. How Do Item Features and User Characteristics Affect Users’ Perceptions of Recommendation Serendipity? A Cross-Domain Analysis. User Modeling and User-Adapted Interaction (UMUAI), December 2022.
  • Lei Li, Yongfeng Zhang, and Li Chen. On the Relationship between Explanation and Recommendation: Learning to Rank Explanations for Improved Performance. ACM Transactions on Intelligent Systems and Technology (TIST), October 2022.
  • Dongning Yan and Li Chen. The Influence of Personality Traits on User Interaction with Recommendation Interfaces. ACM Transactions on Interactive Intelligent Systems (TiiS), July 2022.
  • Li Chen, Wanling Cai, Dongning Yan, and Shlomo Berkovsky. Eye-tracking-based Personality Prediction with Recommendation Interfaces. User Modeling and User-Adapted Interaction (UMUAI), June 2022.
  • Wanling Cai, Yucheng Jin, and Li Chen. Task-Oriented User Evaluation on Critiquing-Based Recommendation Chatbots. IEEE Transactions on Human-Machine Systems, vol. 52(3), pages 354-366, 2022.
  • Li Chen, Dongning Yan, and Feng Wang. User Evaluations on Sentiment-based Recommendation Explanations. ACM Transactions on Interactive Intelligent Systems (TiiS), vol. 9(4), Article 20, 2019.
  • Li Chen, Dongning Yan, and Feng Wang. User Perception of Sentiment-Integrated Critiquing in Recommender Systems. International Journal of Human-Computer Studies (IJHCS), vol. 121, pages 4-20, 2019.
  • Wen Wu, Li Chen, and Yu Zhao. Personalizing Recommendation Diversity based on User Personality. User Modeling and User-Adapted Interaction Journal (UMUAI), vol. 28(3), pages 237–276, 2018.