I am an associate professor of operations research at Cornell University. I received my Ph.D. in mathematics from the University of California, Los Angeles in 2015. My PhD advisors were Wotao Yin and Stefano Soatto.
I am broadly interested in the mathematics of data science, particularly the interplay of optimization, signal processing, statistics, and machine learning.
My research has received several awards, including the INFORMS Optimization Society Young Researchers Prize in (2019), a Sloan Research Fellowship in Mathematics (2020), an NSF CAREER Award (2021), and the SIAM Activity Group on Optimization Best Paper Prize (2023)
CV | Email | Github | Google Scholar
Note: I am on sabbatical until July 2023.
Subgradient methods under weak convexity and tame geometry
Damek Davis, Dmitriy Drusvyatskiy
SIAG/OPT Views and News (2020)
Avoiding saddle points in nonsmooth optimization
Updated (11/2021) | video
Stochastic subgradient method converges on tame functions
Updated (8/2019) | abstract
Nonsmooth and nonconvex optimization under statistical assumptions
Updated (4/2019) | abstract
A nearly linearly convergent first-order method for nonsmooth functions with quadratic growth
Damek Davis, Liwei Jiang
Manuscript (2022)
A superlinearly convergent subgradient method for sharp semismooth problems
Vasileios Charisopoulos, Damek Davis
Mathematics of Operations Research (2023) | code
Asymptotic normality and optimality in nonsmooth stochastic approximation
Damek Davis, Dmitriy Drusvyatskiy, Liwei Jiang
Manuscript (2023)
Active manifolds, stratifications, and convergence to local minima in nonsmooth optimization
Damek Davis, Dmitriy Drusvyatskiy, Liwei Jiang
Manuscript (2022)
Clustering a Mixture of Gaussians with Unknown Covariance
Damek Davis, Mateo Diaz, Kaizheng Wang
Manuscript (2021)
Proximal methods avoid active strict saddles of weakly convex functions
Damek Davis, Dmitriy Drusvyatskiy
Foundations of Computational Mathematics (2021)
Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence
Vasileios Charisopoulos, Yudong Chen, Damek Davis, Mateo Díaz, Lijun Ding, Dmitriy Drusvyatskiy
Foundations of Computational Mathematics (2019) | code
Stochastic model-based minimization of weakly convex functions
Damek Davis, Dmitriy Drusvyatskiy
SIAM Journal on Optimization (2018) | blog
Stochastic subgradient method converges on tame functions
Damek Davis, Dmitriy Drusvyatskiy, Sham Kakade, Jason D. Lee
Foundations of Computational Mathematics (2018)
A Three-Operator Splitting Scheme and its Optimization Applications
Damek Davis, Wotao Yin
Set-Valued and Variational Analysis (2017)
Convergence rate analysis of several splitting schemes
Damek Davis, Wotao Yin
Splitting Methods in Communication and Imaging, Science and Engineering (2017)
Optimization: Structure, Duality, Calculus, and Algorithms
Draft of F’19 notes for my course ORIE 6300
(Last Update: 1/2020)