I am a Postdoctoral Fellow at the Tepper School of Business, Carnegie Mellon University with R. Ravi, with broad interests in designing algorithms that enjoy mathematical guarantees while being practically useful. My research is in discrete optimization and its applications to responsible computing, AI personalization, quantum computing, and online learning. I received my PhD in Algorithms, Combinatorics, and Optimization (ACO) at School of Computer Science, Georgia Tech, and was very fortunate to be advised by Swati Gupta and Mohit Singh.
My thesis introduced and developed the notion of solution portfolios, which are small collections of candidate solutions or algorithms for an optimization problem, with mathematical guarantees. Most optimization frameworks commit to a single objective and return one “best” answer; but in practice different candidates offer different qualities: personalization competes with cost in AI models, different stakeholders want different things, and cost-efficiency competes with fairness. A portfolio instead offers a handful of solutions that provably contain a near-optimal option for any desired objective. You can find my thesis here.
More on my research, all of which is with my fantastic collaborators:
Approximation algorithms: I design approximation algorithms for classical combinatorial optimization problems, usually in multi-objective settings motivated by fairness concerns [SODA 25, Math Prog 26], [EC 23], [arXiv 22] and in stochastic settings [arXiv 26*]. The work on facility location [EC 23] is accompanied by a web tool that documents medical deserts (poor areas with low access to pharmacies and hospitals) in the US and recommends locations for opening new pharmacies.
Responsible AI: I am interested in the trade-offs between cost and personalization/fairness in ML models, and on cost-effective ways of developing diverse LLMs [arXiv 26], leaderboards [arXiv 26*], and policies [ICML 25].
Quantum computing: I am interested in developing hybrid classical-quantum algorithms and how classical techniques can help improve performance on noisy quantum (NISQ) hardware. Specifically, my research develops classical pre-processing methods for QAOA algorithm for QUBO Max-Cut problems, resulting in improved performance and noise reduction in quantum computers [Quantum 26] [Quantum 23] [Physical Review A 22].
Online learning: My research involves using combinatorial techniques to provide improved theoretical guarantees and empirical performance of online algorithms [arXiv 26*] [NeurIPS 21].
* denotes papers under review.
I am on the job market for faculty positions starting in Summer or Fall 2027.
Outside of work, I enjoy poetry, biking, being in nature, following cricket, and cooking.
Research updates
August 2026 — Our paper on noise reduction for QAOA using graph sparsification and decomposition has been published in Quantum. Joint work with Phillip C. Lotshaw, Greg Mohler, and Swati Gupta. Find the paper here.
July 2026 — Our paper on portfolios in combinatorial optimization problems from SODA 25 has been published in Mathematical Progamming. Joint work with Swati Gupta and Mohit Singh. Find the paper (https://arxiv.org/abs/2311.03230).
January 2026 — I am starting as a Postdoctoral Fellow at Tepper School of Business, Carnegie Mellon University!
November 2025 — I defended my PhD thesis titled “New Directions in Multi-Objective Optimization with Applications”! Find the thesis here. Extremely grateful to my thesis committee members: Swati Gupta (co-advisor), Mohit Singh (co-advisor), Santosh Vempala, Milind Tambe, and Sahil Singla.
May 2025 — Our paper on navigating the social welfare frontier with portfolios for multi-objective reinforcement learning has been accepted at ICML 2025! Joint work with Cheol Woo Kim, Shresth Verma, Madeleine Pollack, Lingkai Kong, Milind Tambe, and Swati Gupta. Find the paper here.
May 2025 — I will be attending the 2025 International Conference on Continuous Optimization (ICCOPT) and the International Conference on Machine Learning (ICML) this July. If you’re attending either and would like to chat about research, feel free to reach out!
December 2024 — Our paper on using graph sparsification and decomposition for noise reduction in QAOA is now under revision at Quantum. Joint work with Philip C. Lotshaw, Greg Mohler, and Swati Gupta.
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’ in 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.