Sanket Shah

PhD Student

Harvard University

I am a fourth-year PhD student at Harvard University advised by Prof. Milind Tambe. My current work focuses on Decision-Focused Learning, a paradigm for tailoring a predictive model for a downstream optimization task that uses its predictions.

Previously, I was Research Engineer at Singapore Management University (SMU) advised by Prof. Pradeep Varakantham where I used Reinforcement Learning to solve problems in Transportation and Security. I also spent a year at Microsoft Research India during which I worked on Information and Communications Technology for Development (ICTD) with Dr. Colin Scott and Dr. Bill Thies and Natural Language Processing with Dr. Sundararajan Sellamanickam.

Interests

Algorithmic Decision-Making
AI for Social Good
Machine Learning
Reinforcement Learning

Education

Ph.D. in Computer Science, 2020 - Present

Harvard University
B.E. (Hons.) in Computer Science, 2017

Birla Institute of Technology and Science, Pilani

Recent Publications

Sanket Shah, Arun Suggala, Milind Tambe, Aparna Taneja

May 2023 AAMAS-24

Efficient Public Health Intervention Planning Using Decomposition-Based Decision-Focused Learning

We propose an efficient way to implement decision-focused learning for the kinds of RMABs used for intervention planning in public health.

Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe

February 2023 AAAI-24

Leaving the Nest: Going Beyond Local Loss Functions for Predict-Then-Optimize

We propose two new innovations to help improve the learning of task-specific loss functions.

PDF

Kai Wang, Shresth Verma, Aditya Mate, Sanket Shah, Aparna Taneja, Neha Madhiwalla, Aparna Hegde, Milind Tambe

February 2023 AAAI-23

Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Care Domain

We propose a way to differentiate through MDP Planning for Restless Multi-Armed Bandits. We use this approach to better learn the Transition Matrices from “features” associated with different arms using Decision-Focused Learning.

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Sanket Shah, Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe

December 2022 NeurIPS-22

Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses

We learn task-specific loss functions that, when trained on, allow a predictive model to make better predictions for the given task.

PDF Slides Video

Sanket Shah, Meghna Lowalekar, Pradeep Varakantham

June 2022 In ICAPS-2022

Joint Pricing and Matching for City-Scale Ride-Pooling

We learn how to price in ride-pooling (UberPool) while taking into account the matchings the pricing system induces.

PDF Poster Video

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