Publications — Discrete Optimization
All Discrete Optimization Machine Learning LLMs Algorithmic Fairness Quantum Computing Combinatorics
2026
Stochastic Function Certification with Correlations
Under submission, with Rohan Ghuge and Mohit Singh.
2025
Navigating the Social Welfare Frontier: Portfolios for Multi-objective Reinforcement Learning
ICML, with Cheol Woo Kim, Shresth Verma, Madeleine Pollack, Lingkai Kong, Milind Tambe, Swati Gupta.
Balancing Notions of Equity: Trade-offs Between Fair Portfolio Sizes and Achievable Guarantees
SODA, with Swati Gupta and Mohit Singh.
2024
Promise of Graph Sparsification and Decomposition for Noise Reduction in QAOA: Analysis for Trapped-Ion Compilations
Under revision at Quantum, with Philip C. Lotshaw, Greg Mohler, and Swati Gupta.
2023
Warm-Started QAOA with Custom Mixers Provably Converges and Computationally Beats Goemans-Williamson’s Max-Cut at Low Circuit Depths
Quantum, with Reuben Tate, Bryan Gard, Greg Mohler, and Swati Gupta.
Which $L_p$ norm is the fairest? Approximations for fair facility location across all “$p$”
Economics and Computation (EC), with Swati Gupta and Mohit Singh.
2022
Multi Purpose Routing: New Perspectives and Approximation Algorithms
arXiv, with Majid Farhadi, Prasad Tetali, and Alejandro Toriello.
Generating Target Graph Couplings for QAOA from Native Quantum Hardware Couplings
Physical Review A, with Joel Rajakumar, Bryan Gard, Swati Gupta, and Creston D. Herold.
2021
Reusing Combinatorial Structure: Faster Iterative Projections over Submodular Base Polytopes
NeurIPS, with Hassan Mortagy and Swati Gupta.