Benjamin Grimmer



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I am an assistant professor in the Johns Hopkins Department of Applied Math and Statistics. I am an optimizer. I work on the design and analysis of algorithms for continuous optimization problems beyond the areas where classical theory applies. For example, the selected works below all address foundational issues in optimization theory, bridging the gap between classical approaches and potentially stochastic/nonconvex/nonsmooth/nonLipschitz/adversarial modern problems. Lately, I have found a particular interest in computer-aided design and analysis of optimization methods (a fun meta-type problem, having the computer optimize the algorithms that we use for optimization).

My work is currently supported by AFOSR and a Sloan Fellowship. Previously, I was supported by the NSF during my PhD in Operations Research at Cornell, advised by Jim Renegar and Damek Davis. During my time in grad school, I was privileged to spend Spring 2020 with Google Research working on adversarial optimization and Fall 2017 at UC Berkeley as part of a Simons Institute program bridging continuous and discrete optimization.


Office: N419 Wyman Hall
Email: grimmer at jhu.edu
CV: here
Twitter: @prof_grimmer (mostly sharing pretty 3D prints)


Selected Recent Papers

Accelerated Gradient Descent via Long Steps Youtube, arXiv
Benjamin Grimmer, Kevin Shu, Alex L. Wang.

Some Primal-Dual Theory for Subgradient Methods for Strongly Convex Optimization arXiv
Benjamin Grimmer, Danlin Li.

Radial Duality Part I: Foundations and Part II: Applications and Algorithms Mathematical Programming, 2023
Benjamin Grimmer. arXiv: Part I, Part II

The Landscape of the Proximal Point Method for Nonconvex-Nonconcave Minimax Optimization Mathematical Programming, 2022
Benjamin Grimmer, Haihao Lu, Pratik Worah, Vahab Mirrokni. arXiv


Student Advisees and Collaborators

Ning Liu (PhD Candidate) Johns Hopkins, AMS
Thabo Samakhoana (PhD Candidate) Johns Hopkins, AMS
Alan Luner (PhD Student) Johns Hopkins, AMS
Yue Wu (PhD Student) Johns Hopkins, AMS
Shengyi Yan (Masters) Johns Hopkins, AMS
Raj Gosain (Undergraduate) Johns Hopkins, AMS
Raymond Gong (Undergraduate) Johns Hopkins, AMS