Benjamin Grimmer

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I am a fourth year PhD student in Operations Research at Cornell University, where I am working with Jim Renegar and Damek Davis. I spent Fall 2017 at UC Berkeley as part of a Simons Institute program on continuous and discrete optimization. Prior to coming to Cornell, I completed a BS and MS of Computer Science at the Illinois Institute of Technology, where I worked on a variety of different projects with Professors Ioan Raicu, Gruia Calinescu and Sanjiv Kapoor.

In general, I am interested in the design and analysis of algorithms. My current research focuses on algorithms for continuous optimization problems where very little structure is assumed. In particular, I have recently been focused on solving nonsmooth optimization problems that are outside the scope of the traditional theory. I was awarded an NSF Fellowship in 2017 supporting this research.

Office: 295 Rhodes Hall
Email: bdg79 at

Selected Publications and Working Papers

General Convergence Rates Follow From Specialized Rates Assuming Growth Bounds arXiv
Benjamin Grimmer.

Proximally Guided Stochastic Subgradient Method for Nonsmooth, Nonconvex Problems To appear in SIAM Journal on Optimization
Damek Davis, Benjamin Grimmer. arXiv, Julia

Radial Subgradient Method SIAM Journal on Optimization, 2018
Benjamin Grimmer. arXiv, Julia