Benjamin Grimmer 114 Parker St, Ithaca NY, 14850 Email: bdg79@cornell.edu (918) 991-9888 Web: people.orie.cornell.edu/bdg79/ RESEARCH INTERESTS Machine learning, first-order optimization algorithms, and nonsmooth nonconvex optimization theory. EDUCATION Cornell University, Ithaca, NY PhD in Operations Research and Information Engineering Advisors: James Renegar and Damek Davis August, 2016 – Present Illinois Institute of Technology, Chicago, IL M.S. in Computer Science May, 2016 GPA: 4.00/4.0 Illinois Institute of Technology, Chicago, IL B.S. in Computer Science with a Minor in Applied Mathematics May, 2016 GPA: 3.95/4.0 PUBLICATIONS UNDER REVIEW “Limiting Behaviors of Nonconvex-Nonconcave Minimax Optimization via Continuous-Time Systems” Benjamin Grimmer, Haihao Lu, Pratik Worah, Vahab Mirrokni. “The Landscape of Nonconvex-Nonconcave MinimaxOptimization” Benjamin Grimmer, Haihao Lu, Pratik Worah, Vahab Mirrokni. “A Simple Nearly-Optimal Restart Scheme For Speeding-Up First Order Methods” James Renegar, Benjamin Grimmer. Submitted to Foundations of Computational Mathematics. JOURNAL PUBLICATIONS “Proximally Guided Stochastic Subgradient Method for Nonsmooth, Nonconvex Problems” Damek Davis, Benjamin Grimmer. SIAM Journal on Optimization (2019), 29(3), 1908–1930. “Convergence Rates for Deterministic and Stochastic Subgradient Methods without Lipschitz Continuity” Benjamin Grimmer. SIAM Journal on Optimization (2018), 29(2), 1350–1365. “Radial Subgradient Method” Benjamin Grimmer. SIAM Journal on Optimization (2018), 28(1), 459–469. “Dual-Based Approximation Algorithms for Cut-Based Network Connectivity Problems” Benjamin Grimmer. Algorithmica (2018) 80: 2849-2873. “Improved Approximation Algorithms for Single-Tiered Relay Placement” Gruia Calinescu, Benjamin Grimmer, Satyajayant Misra, Sutep Tongngam, Guoliang Xue, Weiyi Zhang. Journal of Combinatorial Optimization (2016) 31: 1280-1297. CONFERENCE PUBLICATIONS “Nash Equilibrium and the Price of Anarchy in Priority Based Network Routing” Benjamin Grimmer, Sanjiv Kapoor. IEEE Conference on Computer Communications, INFOCOM 2016. “Near Linear Time 5/3-Approximation Algorithms for Two-Level Power Assignment Problems” Benjamin Grimmer, Kan Qiao. In Proceedings of the 10th ACM International Workshop on Foundations of Mobile Computing, FOMC 2014. “Design and Evaluation of the GeMTC Framework for GPU-enabled Many-Task Computing” Scott J. Krieder, Justin M. Wozniak, Timothy Armstrong, Michael Wilde, Daniel S. Katz, Benjamin Grimmer, Ian T. Foster, Ioan Raicu. In Proceedings of the 23rd International ACM Symposium on High Performance Parallel and Distributed Computing, HPDC 2014. WORKSHOP PAPERS AND TECHNICAL REPORTS “Bundle Method Sketching for Low Rank Semidefinite Programming” Lijun Ding, Benjamin Grimmer. OPT-ML 2019. “General Convergence Rates Follow From Specialized Rates Assuming Growth Bounds” Benjamin Grimmer. PATENTS “Analytics for application programming interfaces”. United States Patent: 9,146,787. Qian Zhu, Teresa Tung, Benjamin Grimmer. Filed November 2013, issued September 2015. TALKS The Landscape of Bilinear Minimax Optimization • IIT Discrete Math Seminar, Chicago, IL October 2020 Radial Duality • INFORMS Annual Meeting, Seattle, WA October 2019 • RPI Applied Math Days, Troy, NY April 2019 General Convergence Rates Follow From Specialized Rates Assuming Growth Bounds • INFORMS Annual Meeting, Seattle, WA October 2019 Convergence Rates For Stochastic Subgradient Methods Without Lipschitz Continuity Or Convexity • International Symposium on Mathematical Programming, Bordeaux, France July 2018 • INFORMS Optimization Society, Denver, CO Radial Subgradient Method • INFORMS Annual Meeting, Houston, TX • SIAM Conference on Optimization, Vancouver, Canada TEACHING Instructor • ORIE 3300 (Undergrad): Optimization I, Summer 2020 • ORIE 5270, 6125 (joint Masters and PhD): Big Data Technology and Computational Methods in Operations Research, Spring 2019 Teaching Assistant • ORIE 6300 (PhD): Mathematical Programming I, Fall 2019 • CS 330 (Undergrad): Discrete Structures, Spring 2015 INDUSTRY EXPERIENCE Research Intern Google Research, New York, NY March 2018 October 2017 May 2017 Cornell University Cornell University Cornell University Illinois Institute of Technology Spring 2020 • Worked on solving nonconvex-nonconcave minimax optimization problems relevant to modern machine learning applications like GANs, Reinforcement learning, and robust optimization. • Resulting in two papers on minimax optimization. Software Architecture Intern Summer 2013 Accenture Technology Labs, San Jose, CA • Built a prototype system to log and data mine common patterns from web API traffic. • Resulting system and methods have since been patented. AWARDS, HONORS Received National Science Foundation Graduate Research Fellowship, 2017. Competed in ACM-ICPC (team-based programming competition): • Honorable Mention at the ACM-ICPC 2016 World Finals in Phuket, Thailand. • Competed in the Mid-Central Regional Competition from 2012 to 2015 placing 9th, 6th, 4th, and 3rd (approximately 120 teams competed each year).