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I am a senior researcher at MSR AI4Science, working on machine learning for accelerating computational chemistry. On the ML side, I develop generative models and architectures that can deal with special data structures and constraints (e.g. functional input, symmetry, etc). On the application front, I am interested in molecular dynamics simulation, quantum chemistry, and enhanced sampling methods. If you are interested in collaboration or doing an internship with me, feel free to contact me to have a chat.

I am also a final year PhD candidate at Mila, advised by Aaron Courville.  My PhD work is on probability flows in deep learning, including flow-based models, latent variable models, and diffusion models. I have also worked on designing efficient algorithms for approximate inference and Bayesian deep learning.

See my Google Scholar page for my research.