Mini Lecture Series: Advanced Topics in Graph Representation Learning

Abstract:

Graph representation learning research has grown at an incredible pace in data mining and machine learning communities. This lecture series will cover recent core techniques and advances in graph representation research for modeling a variety of real-world applications and problems, including graph representation, heterogeneous graph mining, graph neural networks, recommendation with graphs, graph-based spatial-temporal learning, and others.

About the Speaker:

Dr. Chao Huang, Assistant Professor, Musketeers Foundation Institute of Data Science (HKU-IDS) and Department of Computer Science, HKU. His research focuses on developing novel machine learning frameworks to tackle various challenges in Data Mining, Information Retrieval, Spatial-Temporal Data Analytics, User Behavior Modeling, Recommendation, Graph Mining, and Deep Representation Learning. Prior to that, he received his Ph.D. in Computer Science from the University of Notre Dame in USA.