About Me

I am a postdoctoral researcher at Toyota Technological Institute at Chicago (TTIC) hosted by Prof. Avrim Blum. Currently, I am supported by Simons Collaboration on the Theory of Algorithmic Fairness. Prior to joining TTIC I did my PhD at University of Maryland College Park where I was advised by Prof. Samir Khuller. I am interested in foundations of machine learning, algorithmic game theory/mechanism design, foundations of responsible computing and theoretical computer science.

Contact: “[firstname]@ttic.edu”

I’m on the 2024-2025 academic job market. Curriculum Vitae

Preprints

Distributional Adversarial Loss with Siddharth Bhandari, Avrim Blum, Chen Dan, Prabhav Jain (arxiv version)

Strategic Filtering for Content Moderation: Free Speech or Free of Distortion? with Avrim Blum, Haifeng Xu, Fan Yao, under submission.

Publications

Strategic Littlestone Dimension: Improved Bounds on Online Strategic Classification with Kunhe Yang, and Hanrui Zhang. NeurIPS 2024, (arxiv version)

Agnostic Multi-Robust Learning Using ERM with Avrim Blum, Omar Montasser and Kevin Stangl. AISTATS 2024, (arxiv version)

Fundamental Bounds on Online Strategic Classification with Avrim Blum and Kunhe Yang. EC 2023, (arxiv version)

Setting Fair Incentives to Maximize Improvement with Hedyeh Beyhaghi, Avrim Blum, and Keziah Naggita. FORC 2023, (arxiv version)

Individual Preference Stability for Clustering with Pranjal Awasthi, Samir Khuller, Matthäus Kleindessner, Jamie Morgenstern, Pattara Sukprasert, Ali Vakilian. ICML 2022.

On Classification of Strategic Agents who Can Both Game and Improve with Hedyeh Beyhaghi, Avrim Blum, and Keziah Naggita. FORC 2022, (arxiv version)

The Landscape of Receptor-Mediated Precision Cancer Combination Therapy: A Single-Cell Perspective SA^*, Pattara Sukprasert^*, Rahulsimham Vegesna, Sanju Sinha, Fiorella Schischlik, Natalie Artzi, Samir Khuller, Alejandro A. Schäffer, and Eytan Ruppin, Nature Communications 2022.( ^* equal contribution) (biorxiv version)(journal version)

The Strategic Perceptron with Hedyeh Beyhaghi, Avrim Blum, and Keziah Naggita. EC 2021, (arxiv version)

An Algorithm for Multi-Attribute Diverse Matching with Faez Ahmed, John P. Dickerson, Mark Fuge, and Samir Khuller. IJCAI 2020, (arxiv version)

Fair Correlation Clustering with Sainyam Galhotra, Barna Saha, and Roy Schwartz, 2020.(arxiv version)

Min-Max Correlation Clustering via Multicut with Samir Khuller, and Barna Saha. IPCO 2019, (conference version)

On Scheduling Coflows with Samir Khuller, Manish Purohit, and Sheng Yang. IPCO 2017. Full version appeared in Algorithmica. (long version)