4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022
Recommendation with Generative Models
machine learning (3353) data mining (553) ������ (8) xiangyu zhao (1)
Xiangyu Zhao is a tenure-track assistant professor of Data Science at City University of Hong Kong (CityU). Prior to CityU, he completed his Ph.D. under the advisory of Prof. Jiliang Tang at DSE Lab of MSU, his M.S. under the advisory of Prof. Enhong Chen at BDAA Lab of USTC, and his B.Eng. under the advisory of Prof. Ming Tang and Prof. Tao Zhou at BigData Center of UESTC.
His current research interests include data mining and machine learning, especially Personalization, Recommender System, Online Advertising, Search Engine, and Information Retrieval Urban Computing, Smart City, GeoAI, Spatio-Temporal Data Analysis, and Location-Based Social Networks Large Language Model, Reinforcement Learning, AutoML, AGI, Graph Learning, Trustworthy AI, and Multimodal ML AI + X: Education, Healthcare, Carbon Neutral, Social Computing, E-commerce, Finance, and Ecosystem
His research has been awarded ICDM'22 and ICDM'21 Best-ranked Papers, Global Top 100 Chinese New Stars in AI, CCF-Ant Research Fund, CCF-Tencent Open Fund, Ant Group Research Fund, Tencent Focused Research Fund, Criteo Faculty Research Award, Bytedance Research Collaboration Program, MSU Dissertation Fellowship, and nomination for Joint AAAI/ACM SIGAI Doctoral Dissertation Award . He serves as top data science conference (senior) program committee members, session chairs and journal reviewers. He serves as
4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022
Recommendation with Generative Models