I am a third-year Ph.D. candidate in the Data Science and Analytics Thrust, Information Hub, at The Hong Kong University of Science and Technology (Guangzhou), supervised by Prof. Wei Wang and co-supervised by Prof. Zhilu Lai.

My research focuses on AI for Science, particularly AI for PDEs, which involves leveraging machine learning to solve partial differential equations (PDEs) in interdisciplinary applications. My interests include techniques such as Physics-Informed Neural Networks (PINNs) and Neural Operators, as well as integrating traditional numerical methods with neural PDE solvers.

In addition to my current work, I have also explored Graph Representation Learning in Recommender Systems, and Knowledge Graphs, with a specific interest in the applications of Hyperbolic Space to these domains.

Research Highlights

• Hybrid neural and numerical methods for PDE solving and discovering.
• Understanding and enhancing neural PDE solver from a mathematical and physical perspective.
• Exploring Knowledge Graphs and Recommender Systems in Non-Euclidean spaces.