Saeed Saremi
Welcome to my personal website! I am a Principal Research Scientist at Genentech, leading a team in Frontier Research. Previously, I was a researcher at UC Berkeley. I finished my PhD in physics at MIT under the supervision of Patrick A. Lee. My research is on generative modeling and the problem of sampling from high-dimensional distributions.
Selected Publications
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Saremi, S., Park, J. W., & Bach, F. (2024). "Chain of log-concave Markov chains".
In Proceedings of the International Conference on Learning Representations.
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Frey, N. C., Berenberg, D., Kleinhenz, J., Hotzel, I., Lafrance-Vanasse, J., Kelly, R. L.,
Wu, Y., Rajpal, A., Ra, S., Bonneau, R., Cho, K., Loukas, A., Gligorijevic, V., & Saremi, S. (2024).
Protein discovery with discrete walk-jump sampling. In International Conference on Learning Representations.
(Outstanding Paper Award)
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O Pinheiro, P. O., Rackers, J., Kleinhenz, J., Maser, M., Mahmood, O., Watkins, A., Ra, S., Sresht, V., & Saremi, S. (2023). 3D molecule generation by denoising voxel grids. Advances in Neural Information Processing Systems, 36.
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Saremi, S., & Srivastava, R. K. (2022). Multimeasurement generative models.
In International Conference on Learning Representations.
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Saremi, S., & Hyvärinen, A. (2019). Neural empirical Bayes.
Journal of Machine Learning Research, 20(181), 1–23.
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Saremi, S., & Sejnowski, T. J. (2013). Hierarchical model of natural images and the origin of scale invariance.
Proceedings of the National Academy of Sciences, 110(8), 3071–3076.
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Saremi, S. (2007). RKKY in half-filled bipartite lattices: Graphene as an example.
Physical Review B, 76(18), 184430.
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Saremi, S., & Lee, P. A. (2007). Quantum critical point in the Kondo-Heisenberg model on the honeycomb lattice.
Physical Review B, 75(16), 165110.
Teaching
- CS 189/289A: Introduction to Machine Learning, UC Berkeley, EECS Department, Fall 2024