Yuanqi Du

Yuanqi Du

PhD Student, Cornell University

Yuanqi Du

Yuanqi Du is a PhD candidate in Computer Science at Cornell University. His research focuses on developing principled and efficient probabilistic and geometric modeling methods that are inspired by, and accelerate, discovery in the natural sciences, spanning chemistry, physics, and biology. His work has appeared at leading machine learning venues (NeurIPS, ICML, ICLR) and in scientific journals including Nature, Nature Machine Intelligence, Nature Computational Science, and the Journal of the American Chemical Society, including three cover articles. He has served as area chairs for machine learning conferences such as NeurIPS and referees for journals such as Nature. During his PhD, he interned at NVIDIA Research and Microsoft Research New England. As a passionate community builder, he has organized over 20 events including conferences, workshops, and seminar series on topics ranging from AI for Science, probabilistic machine learning, and learning on graphs. He leads an educational initiative AI for Science 101. He maintains a slack channel for communication and outreach about AI for Science (with more than 1600 active researchers), feel free to join and say Hi to people here!

I am on the academic job market for positions that start from Fall 2026! You can find my CV here!

Research Interests

  • Probabilistic Machine Learning: Generative Models, Large Language Models, Measure Transport, Stochastic Control, Sampling, Bayesian Inference
  • Structure and Geometry: Neural Architectures (e.g. Graphs and Sets), Equivariance, Symmetry, Tensor Networks
  • AI for Science: Physical Chemistry, Drug Discovery, Materials Science

Additional topics I am interested in include: (Mechanistic) Interpretability, Science of Science, and Societal Impact of AI.

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