Dmitriy Drusvyatskiy

Dmitriy Drusvyatskiy is a Professor in the Department of Mathematics at the University of Washington and holds the Paul Tseng Faculty Fellow title. He also serves as an Adjunct Professor in the Department of Statistics. His research focuses on continuous optimization, particularly in large-scale problems arising in data science, leveraging tools from convex/nonlinear optimization, variational analysis, semi-algebraic geometry, and high-dimensional probability/statistics.

Education: PhD in Operations Research from Cornell University (2013).

Research Interests: His work emphasizes optimization theory and applications, including stochastic optimization, nonsmooth analysis, matrix recovery, and statistical learning. He explores foundational aspects like convergence guarantees, algorithm design, and applications in machine learning and data-driven decision-making.

Notable Trends in Publications: Recent work highlights advancements in stochastic algorithms with geometric step decay, low-rank matrix recovery, and generalization properties of flat minima. His studies often bridge theoretical guarantees with computational efficiency in high-dimensional settings.

• Awards: Paul Tseng Faculty Fellow (2020+).

Advising & Grants: No explicit student advisee list provided. His research is supported by grants focusing on nonsmooth optimization’s structure, complexity, and conditioning. Collaborations span mathematical theory and interdisciplinary applications in data science.