JunJie Wee

Bio

• I am currently a Visiting Assistant Professor in the Department of Mathematics at Michigan State University working with Prof. Guo-Wei Wei. I was previously a Ph.D. candidate at NTU advised by Prof. Kelin Xia on my thesis Geometric and Topological AI for Molecular Sciences. I studied the discrete Ricci curvature and discrete Hodge Laplacian, and applied them to analyse chemical and biological systems. Prior to my Ph.D., I completed my B.Sc. (with Honours) in Mathematical Sciences (with specialization in Applied Mathematics) at NTU, where my honours dissertation on the Korenblum Maximum Principle was completed under Assoc. Prof. Le Hai Khoi.

Research Interests

• My research interests overlap between mathematical biosciences, data science, and artificial intelligence (AI), with an emphasis on applying advanced mathematical frameworks—such as commutative algebra, topology, and differential geometry—to address challenges in molecular biology, materials design, drug discovery, protein engineering and virology.

Illustration of the workflow for predicting deep mutational scanning (DMS) of SARS-CoV-2 S protein RBD-ACE2 complexes using topological deep learning. [Paper, Poster]

Mathematical Foundation of Data Science

• Commutative Algebra, Topological data analysis, Spectral data analysis, Geometric data analysis

Mathematical AI in Molecular Science [Poster]

• Drug design, Protein-protein interactions, Protein engineering, Materials discovery

Mathematical Virology and Therapeutic Discovery

• Virus evolution, Cross-species transmission, Deep mutational scanning [Poster]


• AI-driven therapeutic discovery