Damek Davis

Damek Davis is an Associate Professor of Statistics and Data Science at the University of Pennsylvania's Department of Statistics and Data Science. He serves as Co-Academic Director of the Dual Master's Degree in Statistics. His research focuses on optimization, machine learning, and computational methods, with publications in top-tier journals such as The Annals of Statistics and Mathematical Programming. Davis teaches courses such as STAT4830, which covers optimization for data science and machine learning. His work includes developing algorithms for statistical inference and numerical methods for solving complex optimization problems.

Damek Davis is an Associate Professor of Statistics and Data Science at the Wharton School, University of Pennsylvania. His research focuses on Optimization, Machine Learning, and AI for Math. His work explores stochastic optimization methods, subgradient algorithms, and convergence analysis for nonsmooth and nonconvex problems. He has contributed to the development of splitting schemes, proximal methods, and algorithms for low-rank matrix recovery and phase retrieval. His research emphasizes the interplay between optimization theory and machine learning, with applications in statistical estimation and robust optimization. Davis's publications highlight the convergence properties of stochastic algorithms and their performance on weakly convex and sharp functions.