Neil He Bio

Hi! I’m a first year PhD student in computer science at the University of Illinois Urbana-Champaign (UIUC), advised by Prof. Ge Liu. Previously, I obtained my Bachelors and Masters in Mathematics at Yale University, advised by Prof. Rex Ying and Prof. Menglin Yang. I’m mainly insterested in geometric deep learning, such as generative modelling on Riemannian manifolds and non-Euclidean foundation models, with applications in the natural sciences such as protein synthesis. I’m also broadly interested in exploring how to build foundation models for structured datasets, particularly for real-world applications. Reach out to talk about exciting research ideas, tennis, or reptiles preservations!

News

• Our workshop for non-Euclidean foundation models is accepted at NeurIPS 2025!
• Come to our tutorial for hyperbolic foundation models at SIGKDD 2025! Website Link
• Our paper Efficient Diffusion Models for Symmetric Manifolds is accepted at ICML 2025!
• Our paper Lorentzian Residual Neural Networks is accepted at KDD 2025!