Alex Lew

Assistant Professor of Computer Science

Email

Office Address:

51 Prospect Street
New Haven, CT 06511

Mailing Address:

P.O. Box 208285
New Haven, CT 06520

About Alex Lew

Degrees

  • Ph.D., Massachusetts Institute of Technology
  • S.M., Massachusetts Institute of Technology
  • B.S., Yale University

Perspectives

Alex's research aims to automate and scale up principled probabilistic reasoning, drawing on techniques from programming languages, machine learning, Bayesian statistics, and cognitive science. Alex is especially interested in the theory and practice of probabilistic and differentiable programming languages.

Alex is also a member of the GenLM consortium, a multi-university partnership aiming to better control, compose, and understand language models using the probabilistic programming and Bayesian inference toolkits.

Selected Awards & Honors

  • ACM SIGPLAN Distinguished Paper Award (POPL)
  • ACM SIGLOG Distinguished Paper Award (LICS)
  • Probability and Programming Research Award (Meta)

Selected Publications

  • Loula, J., LeBrun, B., Du, L., Lipkin, B., Pasti, C., Grand, G., Liu, T., Emara, Y., Freedman, M., Eisner, J., Cotterell, R., Mansinghka, V.K., Lew, A.K., Vieira, T., & O’Donnell, T. Syntactic and semantic control of large language models via sequential Monte Carlo. ICLR 2025.
  • Bowers, M.*, Lew, A.K.*, Tenenbaum, J.B., Solar-Lezama, A., & Mansinghka, V.K. Stochastic lazy knowledge compilation for inference in discrete probabilistic programs. PLDI 2025.
  • Becker, M.*, Lew, A.K.*, Wang, X., Ghavami, M., Huot, M., Rinard, M., & Mansinghka, V.K. Probabilistic programming with programmable variational inference. PLDI 2024.
  • Huot, M.*, Lew, A. K.*, Mansinghka, V. K., & Staton, S. ωPAP spaces: Reasoning denotationally about higher-order, recursive probabilistic and differentiable programs. LICS 2023.
  • Lew, A. K., Ghavamizadeh, M., Rinard, M., & Mansinghka, V. K. Probabilistic programming with stochastic probabilities. PLDI 2023.
  • Lew, A. K.*, Matheos, G.*, Zhi-Xuan, T., Ghavamizadeh, M., Gothoskar, N., Russell, S., & Mansinghka, V. K. SMCP3: Sequential Monte Carlo with probabilistic program proposals. AISTATS 2023.
  • Lew, A. K.*, Huot, M.*, Staton, S., & Mansinghka, V. K. ADEV: Sound automatic differentiation of expected values of probabilistic programs. POPL 2023.
  • Lew, A. K., Cusumano-Towner, M., & Mansinghka, V. K. Recursive Monte Carlo and variational inference with auxiliary variables. UAI 2022.
  • Lew, A. K., Agrawal, M., Sontag, D., & Mansinghka, V. K. PClean: Bayesian data cleaning at scale with domain-specific probabilistic programming. AISTATS 2021.
  • Lew, A. K., Cusumano-Towner, M. F., Sherman, B., Carbin, M., & Mansinghka, V. K. Trace types and denotational semantics for sound programmable inference in probabilistic languages. POPL 2020.
  • Cusumano-Towner, M. F., Saad, F. A., Lew, A. K., & Mansinghka, V. K. Gen: a general-purpose probabilistic programming system with programmable inference. PLDI 2019.