معرفی
Alex Wein is an Assistant Professor of Mathematics at the University of California, Davis. His research focuses on theoretical computer science, statistics, probability, and data science, with an emphasis on computational complexity of statistical inference, particularly in low-degree polynomial models. He explores challenges in tensor analysis, Bayesian inference, and group actions such as cryo-electron microscopy. His work bridges statistical physics and algorithmic hardness, contributing to foundational understanding of estimation and recovery thresholds.
Education:
- Ph.D. in Mathematics, Massachusetts Institute of Technology (2018)
Research Interests:
- Optimal algorithms for hidden structure detection in noisy data
- Low-degree polynomial framework for algorithmic hardness predictions
- Tensors and their computational challenges
- Connections between Bayesian methods and statistical physics
Recent Talks:
- 'Sharp Phase Transitions in Estimation with Low-Degree Polynomials' at SLMath (2025)
- 'Unifying Statistical Physics and Low-Degree Polynomials?' at Les Houches School of Physics (2025)
۰مقاله منتشرشده
