Keynote Speakers
Dr. Alexandros Karatzoglou
Dr. Alexandros Karatzoglou is currently a Research Scientist at Google in London, and previously the director of Research at Telefonica in Barcelona. He spent many years between Vienna and Canberra working on his Ph.D. on kernel methods and open-source software. He started working on recommender systems right after his PhD, introducing ranking techniques for collaborative filtering, tensor-based context-aware collaborative filtering, and session-based recommendations. Alexandros currently work on reinforcement learning for recommender systems and interactive recommendations.
Keynote Speakers
Dr. Li Chen
Dr. Li Chen is currently an Associate Professor in Department of Computer Science at Hong Kong Baptist University (HKBU). She obtained her PhD degree in Computer Science from Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland, and Bachelor and Master degree from Peking University, China. Her recent research focus has mainly been on recommender system design and development, which integrates approaches of multiple disciplines including artificial intelligence, human-computer interaction, user modeling, and user behavior analytics. The application domains cover social media, e-commerce, and online education. She has authored and co-authored over 100 publications, most of which have appeared in refereed high-impact journals and conferences, with over 5,000 citations so far. Her co-authored paper receives UMUAI 2018 James Chen Best Paper Award. She is now ACM senior member, steering committee member of ACM Conference on Recommender Systems (RecSys), editorial board member of User Modeling and User-Adapted Interaction Journal (UMUAI), editorial board member of Journal of Intelligent Information Systems (JIIS), and associate editor of ACM Transactions on Interactive Intelligent Systems (TiiS).
Keynote Speakers
Dr. Yong Zheng
Dr. Yong Zheng is currently a tenure-track Assistant Professor at the Department of Information Technology and Management, College of Computing, Illinois Institute of Technology, Chicago, USA. He obtained his PhD degree in computer and information sciences from DePaul University in Chicago. The topic of his PhD thesis fell in the area of context-aware recommender systems. His research interests lie in Recommender Systems, Context-Awareness, Human Factors, Technology-Enhanced Learning, and so forth. He served in the organization committee in ACM RecSys 2018, ACM UMAP 2018 - 2020, and ACM IUI (2018, 2019, 2021).
