معرفی
Damek Davis is a Visiting Associate Professor at the Wharton Department of Statistics and Data Science at the University of Pennsylvania and an Associate Professor of Operations Research at Cornell University (currently on leave). He held NSF Postdoctoral Fellowships and completed his PhD in Mathematics at UCLA under Wotao Yin and Stefano Soatto.
His research bridges optimization, machine learning, statistics, and signal processing, with a focus on convergence guarantees for stochastic and nonsmooth optimization methods. He has developed accelerated gradient descent algorithms, characterized SGD behavior in nonconvex settings, and formalized avoidance of strict saddle points in proximal methods.
Key publications include exponential accelerations of gradient-based techniques and first guarantees for SGD on weakly convex functions. His work has been recognized by the
- Sloan Research Fellowship
- INFORMS Optimization Society Young Researchers Prize
- NSF CAREER Award
- SIAM Activity Group on Optimization Best Paper Prize
Davis actively advises Penn graduate students and serves as an associate editor at Mathematical Programming and Foundations of Computational Mathematics. He emphasizes clear technical writing and public communication, maintaining a blog and lecture notes on optimization theory.
