About
I am an Assistant Professor at the Department of Computer Science and Engineering at IIT Bombay, and a member of C-MInDS (Centre for Machine Intelligence and Data Science) at IIT Bombay.
Prior to joining IIT Bombay, I was a postdoctoral researcher at FAIR Labs (Meta) working with Max Nickel on socially responsible recommendation systems. Before that, I was a postdoctoral fellow at the Data Science Institute at Columbia University, hosted by Prof. Yash Kanoria and Prof. Tim Roughgarden. I completed my PhD from the Department of Computer & Information Science at the University of Pennsylvania, under the guidance of Prof. Shivani Agarwal.
Research Agenda
My research lies at the intersection of machine learning, artificial intelligence, and human decision-making. I am broadly interested in understanding and improving how humans interact with ML/AI systems such as recommenders and agentic systems.
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Dynamics of Human-AI Interaction — feedback loops in recommendations, adaptive preferences, and long-term engagement vs. utility trade-offs. [ALT’24, FAccT’24, WINE’25, ICLR’26, NeurIPS’22]
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Learning from Human Feedback — algorithms that learn from pairwise comparisons, choice behavior, and noisy or adversarial responses, including dueling bandits, ranking, and peer prediction. [NeurIPS’22, ICML’22, TMLR’25, NeurIPS’20, ICML’20, ICML’18, EC’17]
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Responsible AI Design — model calibration, creator incentives on platforms, and benchmarking of LLMs and agentic systems. [AISTATS’26, FAccT’24, TEAC’20]
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Algorithms & ML Theory — submodular optimization, stochastic bandits, streaming and parallel algorithms. [NeurIPS’24, FOCS’24, SODA’24, COLT’22, SODA’19]
See the full Research page for more details.
Recent Highlights
- [AISTATS 2026] “Creator Incentives in Recommender Systems” — Selected for Oral Presentation (top 10 out of ~2100 submissions).
- [ICLR 2026] “Ads that Stick: Near-Optimal Ad Optimization through Psychological Behavior Models.”
- [FOCS 2024] “Semi-Bandit Learning for Monotone Stochastic Optimization.”
- [FAccT 2024] “System-2 Recommenders: Disentangling Utility and Engagement.”
I am looking for motivated PhD students and pre-doctoral researchers interested in machine learning theory, human-AI interaction, and responsible AI. If you are interested, please reach out via email with your CV and a brief description of your research interests.