Scholar
Alexander K. Lew
Google Scholar ID: TiF1WEsAAAAJ
Assistant Professor, Yale University
Citations & Impact
Citations
788
H-index
12
i10-index
15
Publications
20
Co-authors
12
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Selected Publications:
- - Fast Controlled Generation from Language Models via Adaptive Weighted Rejection Sampling, COLM 2025, outstanding paper
- - Stochastic Lazy Knowledge Compilation for Inference in Discrete Probabilistic Programs, PLDI 2025
- - Syntactic and Semantic Control of Large Language Models via Sequential Monte Carlo, ICLR 2025, selected for oral presentation
- - Probabilistic Programming with Programmable Variational Inference, PLDI 2024
- - ωPAP Semantics: Reasoning Denotationally About Higher-Order, Recursive Probabilistic and Differentiable Programs, LICS 2023, distinguished paper
- - Probabilistic Programming with Stochastic Probabilities, PLDI 2023
- - ADEV: Sound Automatic Differentiation of Expected Values of Probabilistic Programs, POPL 2023, distinguished paper
- - SMCP³: Sequential Monte Carlo with Probabilistic Program Proposals, AISTATS 2023
- - Recursive Monte Carlo and Variational Inference with Auxiliary Variables, UAI 2022
- - PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming, AISTATS 2021, selected
Research Experience
- Position: Assistant Professor, Yale University Department of Computer Science. Research Projects: Developing theoretical foundations, compilers, and high-level tools for automating and speeding up probabilistic programming.
Education
- Insufficient information
Background
- Research Interests: Automating and scaling up principled probabilistic reasoning, similar to how tools like TensorFlow and PyTorch have automated and scaled up deep learning. Professional Field: Computer Science. Brief Introduction: Starting Fall 2025, will be joining Yale’s Computer Science department as an Assistant Professor.
Miscellany
- Personal Interests: Open to PhD or postdoc candidates interested in probabilistic and differentiable programming.
