Professor, University of Science and Technology of China

Research Area: Recommender System, Data Mining, Artificial Intelligence

Award Citation: The AYSF Committee acknowledges his contribution to the development of the deep learning-based and graph-based recommender systems which demonstrate the ability of capturing the complex dynamics of user-item interactions and emphasizing high-order user-item connectivity, and would like to support his exploration of the next frontier of human-centric AI focusing on personalized foundation models.

Bio: Xiangnan He is a professor at the University of Science and Technology of China. He received his Ph.D. from the National University of Singapore (NUS) in 2016. His research interests span information retrieval, data mining, and machine learning. He has published over 100 papers on top-tier conferences and journals like SIGIR, WWW, KDD, IEEE TKDE and ACM TOIS, with over 60,000 citations and an H-index of 109. He is the recipient of Alibaba DAMO Academy Young Fellow, and his work has received the Outstanding Paper Award in ICLR 2025, the Frontiers of Science Award in International Congress of Basic Science, and Best Paper Honorable Mention in SIGIR 2023 and 2021. He serves as an Associate Editor for IEEE TKDE, IEEE TBD and ACM TOIS, and an Area Chair for SIGIR, WWW, NeurIPS, etc.

Personal Web: http://staff.ustc.edu.cn/~hexn/