I am a PhD student in Algorithms, Combinatorics, and Optimization (ACO) at the School of Computer Science, Georgia Tech, and currently visiting MIT Sloan School of Management. I am fortunate to be advised by Dr. Swati Gupta and Dr. Mohit Singh.
My research interests include discrete optimization and its applications to algorithmic fairness [SODA25] [EC23] [web-tool], machine learning [NeurIPS21], and quantum computing [Quantum23] [PRA22] [arXiv24].
Much of my research seeks to understand inherent trade-offs in optimization and learning problems: for example, the trade-off between algorithm runtime and regret in online learning problems, or the trade-off between “fairness” and “efficiency” (or between various fairness notions) in resource allocations/machine learning problems. While algorithm designers often focus on optimizing for one of these objectives – assuming that it is given a priori – real-world applications often require balancing multiple (often complex) objectives. I am interested in understanding the fundamental limits of such trade-offs and designing practical algorithms that allow for a flexible balance between these objectives.
My research in quantum computing focuses on developing hybrid quantum-classical algorithms for combinatorial optimization problems, applying classical algorithmic techniques to improve the performance of quantum algorithms.
I am currently on the job market for post-doc positions for Spring 2026/Fall 2025.
Research updates
October 2024
Our paper on portfolios for fairness in combinatorial optimization has been accepted at SODA 2025! Joint work with Swati Gupta and Mohit Singh. Find the paper here.
September 2024
I am visiting Dr. Swati Gupta’s lab at MIT Sloan School of Management this Fall!
June 2024
Our paper on using graph sparsification and decomposition for noise reduction in QAOA is now online here. Joint work with Philip C. Lotshaw, Greg Mohler, and Swati Gupta.
May 2024
Our web tool to visualize and mitigate ‘medical deserts’ the US is now online. Based on our paper on fair facility location from EC 2023. Joint work with Swati Gupta and Mohit Singh.
May 2024
I am interning at Amazon Research in Bellevue, Washington this summer with the Supply Chains Optimization Technology team.
September 2023
Our paper Warm-Started QAOA with Custom Mixers Provably Converges and Computationally Beats Goemans-Williamson’s Max-Cut at Low Circuit Depths has been published in Quantum! Find the paper here. Joint work with Reuben Tate, Bryan Gard, Greg Mohler, and Swati Gupta.
July 2023
Our paper Which $L_p$ norm is the fairest? Approximations for fair facility location across all ‘p’ has been published in Economics and Computation (EC) 2023! Find the paper here. Joint work with Swati Gupta and Mohit Singh.
July 2022
Our paper Generating Target Graph Couplings for QAOA from Native Quantum Hardware Couplings has been accepted for publication in Physical Review A! Find the paper here. Joint work with Joel Rajakumar, Bryan Gard, Creston Herold, and Swati Gupta.
May 2022
Our poster on Reusing Combinatorial Structure: Faster Iterative Projections over Submodular Base Polytopes is runner-up at MIP 2022 poster competition! Find the paper from NeurIPS 2021 here. Joint work with Hassan Mortagy and Swati Gupta.
February 2022
Our paper New Proofs for the Disjunctive Rado Number of the Equations $x_1 - x_2 = a$ and $x_1 - x_2 = b$ has been published in Graphs and Combinatorics! Find the paper here. Joint work with A. Dileep and Amitabha Tripathi.
December 2021
Our paper Reusing Combinatorial Structure: Faster Iterative Projections over Submodular Base Polytopes has been published in NeurIPS 2021! Find the paper here. Joint work with Hassan Mortagy and Swati Gupta.