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.
I completed my B.Tech from Meghnad Saha Institute of Technology, Kolkata under West Bengal University of Technology in 2013.
News
2024
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I will be returning as an Applied Scientist intern to Amazon AWS AI in the summer of 2024.
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Our paper SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits was accepted at AISTATS 2024.
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My internship at Amazon AWS AI has been extended (as part-time) till February 2024.
2023
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I won the Neural Information Processing Systems (Neurips) 2023 top reviewer award.
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I passed my prelim exam for the Doctoral degree.
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Our paper Multi-task Representation Learning for Pure Exploration in Bilinear Bandits was accepted at Neurips 2023.
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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.
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I won the top reviewer award at Uncertainty in Artificial Intelligence (UAI) 2023.
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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.
2022
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Our paper ReVar: Strengthening Policy Evaluation via Reduced Variance Sampling was accepted at Uncertainty in Artificial Intelligence (UAI) 2022.
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Our paper Safety Aware Changepoint Detection for Piecewise i.i.d. Bandits was accepted at Uncertainty in Artificial Intelligence (UAI) 2022.
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I passed my Qualification Exam for the Doctoral degree.
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Our paper Chernoff Sampling for Active Testing and Extension to Active Regression was accepted at Artificial Intelligence and Statistics (AISTATS) 2022.
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Our paper Nearly Optimal Algorithms for Level Set Estimation was accepted at Artificial Intelligence and Statistics (AISTATS) 2022.
2021
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I got Master’s Degree in Electrical Engineering from UW-Madison. Now moving on to finish my doctoral degree.
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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).
2020
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Our paper Generalized Chernoff Sampling: A New Perspective on Structured Bandit Algorithms”, was accepted at Theoretical Foundations Of Reinforcement Learning ICML 2020 Workshop.
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Our paper A Unified Approach to Translate Classical Bandit Algorithms to the Structured Bandit Setting was accepted in IEEE Journal on Selected Areas in Information Theory (2020).
2019
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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.
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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.
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I received the 2019 Chancellor’s Opportunity Fellowship award at the University of Wisconsin-Madison.
Resume
You can find my full resume here (Resume).
Contact
smukherjee27 [at] wisc [dot] edu