Zhang Wan

I am a Ph.D. student at the University of Manchester, UK, fortunately supervised by Dr. Tingting Mu and Prof. Samuel Kaski. Previously, I was a master’s student studying artificial intelligence at Nanyang Technological University, Singapore, under the supervision of Prof. Chee-Keong Kwoh. I received my B.Sc. from the University of Birmingham, UK, and my B.Eng. from the Harbin Institute of Technology, China, in 2022.

My website: https://zhangwan-byte.github.io/

My current interest lies in exploring distribution shifts across various scales, for which a narrow meaning draws on dealing with the broken i.i.d. assumption whose synonyms include extrapolation, domain adaptation, etc. In a broader sense, I am interested in situations where classic assumptions are either invalid or irrelevant, due to generalised/specific cases (e.g. domain-specific assumptions) and external effects (e.g. varying observation or environment). These scenarios often necessitate additional assumptions to impose extra structures, offering insights on how to model things in change and constancy.

I am also interested in the following topics:

• Machine Learning: geometric deep learning, dimensionality reduction, visualisation, human-in-the-loop, reinforcement learning, etc.
• AI for Science: drug discovery, earth science, bioinformatics, etc.

Several subfields of (applied) math play significant roles in my research or personal interests, e.g., optimal transport, (random) graph theory, Riemannian geometry, functional analysis, etc. Exploring more than exploiting as an early-stage researcher. Recent trending topics are also interesting to me. Feel free to contact me for any discussion!