Speaker：Prof. Li Chen, Hong Kong Baptist University

Time： Dec. 10, 10 a.m.

Venue：Room 1113, Wangkezhen Building

Host：Tonglin Jiang

Abstract

Recent advances in AI technologies have led to the development of more innovative applications prioritizing human well-being across various dimensions, including emotional, cognitive, and social aspects. In this talk, I will present our efforts to leverage three technologies—personalized recommendation systems, conversational AI, and generative AI—to create personal assistants that support music exploration, self-awareness, and reminiscence. Our studies illuminate how different interaction techniques and user characteristics influence trust in and willingness to use these AI assistants. Additionally, we will discuss design considerations that can enhance the system's effectiveness in promoting mental well-being by tailoring its functionalities and user interactions to the preferences and needs of diverse populations, including young people and older adults. By integrating insights from multiple disciplines—such as AI, human-computer interaction, psychology, and cognitive sciences—our ultimate goal is to develop more robust AI-empowered systems that actively support mental health.

Bio

Prof. Li Chen is currently a Professor and Associate Head (Research) in the Department of Computer Science at Hong Kong Baptist University (HKBU), China. She obtained her PhD degree in Computer Science from the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland, and a Bachelor's degree in Computer Science and a Master's degree in Computer Software and Theory from Peking University, China. Her research areas include conversational AI, explainable AI, recommender systems, and human-computer interaction, along with their applications in diverse domains, particularly psychological well-being in recent years. She has co-authored over 150 publications, with 10,600 citations so far (H-index 49). 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 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 the founding 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.