Organizers

• Dr. Irene Li (ireneli@ds.itc.u-tokyo.ac.jp) is a Project Assistant Professor at the University of Tokyo. Her main research interests lie in natural language processing and artificial intelligence, with a specific focus on medical and clinical texts as well as educational applications. She publishes and serves on the program committee for top conferences, including ACL, NANAC, EMNLP, AAAI, among others. Additionally, she serves as the principal organizer of both online and offline seminars, one of which attracted approximately 300 registrations. She was also among the authors of the Best Student Paper Award at RecSys 2023.
• Dr. Ruihai Dong (ruihai.dong@ucd.ie) is an Assistant Professor at the University College of Dublin. His research interests lie in Machine Learning and Deep Learning, and their applications in recommender systems and finance. Ruihai has published in top peer-reviewed journals and leading conferences such as WWW, RECSYS, IUI, ACL, IJCAI, etc., and also has served on the program committee for various conferences, including ACL, AAAI, ECML, EMNLP, etc. He was also a co-author of the Best Student Paper Award at RecSys 2023. He was a founder and organizer of the Deep Learning meetup in Dublin and organized a series of events sponsored by multiple industry supporters, including Zalando, Accenture, Deloitte, etc.
• Dr. Lei Li (csleili@comp.hkbu.edu.hk) is a Post-doctoral Research Fellow at Hong Kong Baptist University. His research interests lie in recommender systems and natural language processing. Recently, he has been investigating large language models (LLM) for recommender systems, which has been supported by Hong Kong Research Grants Council (RGC) since 2022. His research outcome on this topic includes LLM-based explainable recommendation, efficient LLM for recommendation, and a survey of LLM-based recommendation. He served as a PC member for RecSys and WWW, as a reviewer for journals such as TKDE, TOIS, TORS, and TBD, and as a guest editor for a special issue of TORS entitled "Large Language Models for Recommender Systems". He also did a tutorial presentation about LLM-based recommendations at RecSys in 2023, titled Large Language Models for Recommendation, which attracted hundreds of audiences.
• Prof. Li Chen (lichen@comp.hkbu.edu.hk) is a Professor and Associate Head (Research) of the Department of Computer Science at Hong Kong Baptist University. Professor Chen’s recent research focus has mainly been on personalized 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, 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), recommender systems (ACM RecSys), user modeling (UMAP), and intelligent user interfaces (CHI, IUI, Interact). She has served as a Journal Editor and Conference organizer in a number of leading journals and conferences, such as General Co-chair of RecSys 2023, Track Co-chair of UMAP'23, etc.