Subhojyoti Mukherjee

I am a Ph.D. candidate from Fall 2019 in the Department of Electrical and Computer Engineering (ECE), University of Wisconsin-Madison. I am advised by Dr. Robert Nowak, Dr. Josiah Hanna, and Dr. Qiaomin Xie. I am a graduate research assistant at Wisconsin Institute of Discovery. I work in the area of Reinforcement Learning, Active learning, and Multi-armed bandits. Recently I have also started working on incorporating active learning strategies for Large Language Models.

I was an M.S (Research) scholar in the Computer Science and Engineering Department, IIT Madras from January 2015 to July 2018. I was advised by Dr. Balaraman Ravindran (CSE Department, IIT Madras) and Dr. Nandan Sudarsanam (Department of Management Studies, IIT Madras). I was associated with the RISE lab at IIT Madras. I worked in the area of stochastic and non-stochastic Multi-Armed Bandit settings.

News

Our paper SaVeR: Optimal Data Collection Strategy for Safe Policy Evaluation in Tabular MDP was accepted at ICML 2024.
I will be returning as an Applied Scientist intern to Amazon AWS AI in the summer of 2024.
Our paper SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits was accepted at AISTATS 2024.
My internship at Amazon AWS AI has been extended (as part-time) till February 2024.

I won the Neural Information Processing Systems (Neurips) 2023 top reviewer award.
I passed my prelim exam for the Doctoral degree.
Our paper Multi-task Representation Learning for Pure Exploration in Bilinear Bandits was accepted at Neurips 2023.
Our paper SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits was accepted at ICML 2023 Workshop The Many Facets of Preference-Based Learning.
I won the top reviewer award at Uncertainty in Artificial Intelligence (UAI) 2023.
I worked at the intersection of Active Learning and Large Language Models (LLMs) in my internship at Amazon AWS AI in the summer 2023. My internship has been extended (as part-time) till the end of Fall 2023.

Our paper ReVar: Strengthening Policy Evaluation via Reduced Variance Sampling was accepted at Uncertainty in Artificial Intelligence (UAI) 2022.
Our paper Safety Aware Changepoint Detection for Piecewise i.i.d. Bandits was accepted at Uncertainty in Artificial Intelligence (UAI) 2022.
I passed my Qualification Exam for the Doctoral degree.
Our paper Chernoff Sampling for Active Testing and Extension to Active Regression was accepted at Artificial Intelligence and Statistics (AISTATS) 2022.
Our paper Nearly Optimal Algorithms for Level Set Estimation was accepted at Artificial Intelligence and Statistics (AISTATS) 2022.

I got Master’s Degree in Electrical Engineering from UW-Madison. Now moving on to finish my doctoral degree.
Our paper A Unified Approach to Translate Classical Bandit Algorithms to the Structured Bandit Setting was accepted in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 21).

Our paper Distribution-dependent and Time-uniform Bounds for Piecewise i.i.d Bandits was accepted at Reinforcement Learning for Real Life ICML 2019 Workshop.
Going to spend the summer of 2019 as a Research Associate in the Department of Electrical and Computer Engineering (ECE) at Carnegie Mellon University (CMU) working with Professor Gauri Joshi and Osman Yagan.
I received the 2019 Chancellor’s Opportunity Fellowship award at the University of Wisconsin-Madison.

You can find my full resume here (Resume).

smukherjee27 [at] wisc [dot] edu