Arnesh M. Sujanani
Chinese University of Hong Kong. Department of Computer Science and Engineering.
Office: MC 5461
200 University Avenue West
Waterloo, Ontario
I am currently on a three-month appointment working with Professor Songtao Lu in the Department of Computer Science and Engineering at The Chinese University of Hong Kong. I am interested broadly in optimization for machine learning and quantum, continuous optimization, semidefinite programming, scientific computing, and numerical linear algebra. The main focus of my research is to develop scalable, fast, and parameter-free first order-methods for large-scale optimization problems with provable convergence guarantees.
From September 2024 to September 2026, I was a postdoctoral fellow at University of Waterloo’s Department of Combinatorics and Optimization where I primarily worked with Saeed Ghadimi and Henry Wolkowicz. In Summer 2024, I received my PhD in Operations Research from Georgia Tech ISyE where I was advised by Renato D.C. Monteiro. I also received my M.S. in Mathematics in Spring 2024 from Georgia Tech and a B.S. in Applied and Computational Mathematics in Spring 2019 from University of Southern California.
news
| Apr 29, 2026 | The paper ``A low-rank augmented Lagrangian method for large-scale semidefinite programming based on a hybrid convex-nonconvex approach’’ has been published online in Mathematical Programming. |
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| Oct 14, 2025 | The paper ``cuHALLaR: A GPU Accelerated Low-Rank Augmented Lagrangian Method for Large-Scale Semidefinite Programming’’ has been submitted to Mathematical Programming Computation. |
| Sep 14, 2025 | The paper ``Asymptotically Fair and Truthful Allocation of Public Goods’’ has been accepted to Journal of Artificial Intelligence Research. |
| Jun 09, 2025 | The paper ``Efficient Parameter-Free Restarted Accelerated Gradient Methods for Convex and Strongly Convex Optimization’’ has been published online in Journal of Optimization Theory and Applications. |
