Souradip Chakraborty

Souradip Chakraborty

CS PhD@UMD, Reinforcement Learning

About Me

I’m Souradip, a 3rd year CS Ph.D. student at the University of Maryland, working on the Foundations of trustworthy reinforcement Learning, with a focus on developing safe, reliable, deployable & provable RL methods for real-world applications such as robotics, healthcare, finance, etc, working with Prof. Furong Huang, Prof. Dinesh Manocha (UMD) and in close collaboration with Prof. Mengdi Wang (Princeton), Prof. Amrit Singh Bedi (UCF), Alec Koppel (AI Research Head, JP Morgan Chase & Co).

My latest research focuses on designing a reliable and unified framework for RLHF by characterizing the dependence of policy-driven data on alignment objectives PARL. I am particularly interested in the statistical understanding of learning from preferences by examining the biases inherent in preference data and its long-term ethical considerations, and societal impacts.

Recent News

  1. Our latest research PARL characterized a major gap in the current Alignment framework with RLHF by characterizing the distribution shift and received significant attention Reference
  2. Our timely survey provides crucial insights into AI-generated text recognition - Current state and Open problems Media Coverage
  3. Excited to deliver a Tutorial on Reward Design and Reinforcement Learning from Human Feedback at PyImageSearch, Kaggle
  4. Glad to receive Top Reviewer Award at NeurIPS2023 (2nd time in a row).
  5. Our latest research on the Possibilities of AI Text Detection got significant attention in the community and media coverage Reference Media Coverage
  6. Served as one of the student organizers of summer AI camps at UMD Fall’23 as a part of the Iribe Initiative for Inclusion and Diversity with the AI4ALL and Maryland Center for Women in Computing.

Selected Publications

  1. Souradip Chakraborty, Amrit Singh Bedi, Sicheng Zhu, Bang An, Dinesh Manocha, Furong Huang On the Possibilities of AI-Generated Text Detection
  2. Souradip Chakraborty, Kasun Weerakoon, Prithvi Poddar, Pratap Tokekar, Amrit Singh Bedi, Dinesh Manocha RE-MOVE: An Adaptive Policy Design Approach for Dynamic Environments via Language-Based Feedback
  3. Xiangyu Liu, Souradip Chakraborty, Yanchao Sun, Furong Huang Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in Multi-Agent RL (Outstanding Paper Award)
  4. Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Mengdi Wang, Furong Huang, Dinesh Manocha STEERING: Stein Information Directed Exploration for Model-Based Reinforcement Learning, ICML 2023
  5. Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Brian M. Sadler, Furong Huang, Pratap Tokekar, Dinesh Manocha Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning, Oral, AAAI 2023
  6. Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Pratap Tokekar, Dinesh Manocha, Dealing with Sparse Rewards in Continuous Control Robotics via Heavy-Tailed Policy Optimization, ICRA 2023
  7. Souradip Chakraborty, Kasun Weerakoon, Nare Karapetyan, Adarsh Jagan Sathyamoorthy, Amrit Singh Bedi, Dinesh Manocha HTRON: Efficient Outdoor Navigation with Sparse Rewards via Heavy Tailed Adaptive Reinforce Algorithm, CoRL 2022
  8. Amrit Singh Bedi, Souradip Chakraborty, Anjaly Parayil, Brian Sadler, Pratap Tokekar, Alec Koppel On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces, ICML 2022 Spotlight

Selected Patents

  1. Gregory Dixon, Souradip Chakraborty, Ojaswini Chhabra, Mallikharjuna Mv: Reverse Engineering Food Ingredient Share estimation using Constrained Optimization, US Patent, Walmart Ref. 6031US01.
  2. Souradip Chakraborty, Abhishek Mishra, Somedip Karmakar: Systems and methods for Unsupervised image processing, US Patent, Ref. US11688049B2.
  3. Pranay Dugar, Souradip Chakraborty: Automated planogram anomaly detection with Computer Vision, US Patent, Ref. US11669843B2.
  4. Souradip Chakraborty, Mani Garlapati: Systems and methods for identifying negotiable items, US Patent, Walmart Ref. 5928US01.
  5. Souradip Chakraborty, Rajesh Shreedhar Bhat, Mani Garlapati System and Method For Automated Electronic Catalogue Management and Image Quality Assessment, US Patent, Walmart Ref. 5118US01.

Broader Impact & Open-Source Contributions

  1. Served as one of the student organizers of summer AI camps at UMD Fall’23 as a part of the Iribe Initiative for Inclusion and Diversity with the AI4ALL and Maryland Center for Women in Computing
  2. Outstanding Reviewer Award (Travel award) at Neurips 2022 and Neurips 2023 (consecutive 2years in a row)
  3. Outstanding Reviewer Award (Travel award) at AISTATS 2023
  4. Recognized by Google as a Google Developer Expert in Machine Learning for my open-source contributions & mentorships in the field of AI and ML.
  5. AI vs COVID-19 BioMedical Research Initiaive with Google Research : Developed BioMedBERT for biomedical researchers, doctors, and virologists, to augment their ability to sift through biomedical knowledge and existing research to extract novel insights and help them make new drug discoveries, COLING’2019

Selected Blogs & Articles

  1. Souradip Chakraborty, Amlan Das, Sai Yashwanth: Risks and Caution on Applying PCA for Supervised Learning Problems, published on Towards Data Science, Medium, 2019.
  2. Souradip Chakraborty, Rajesh Shreedhar Bhat: Why Not Mean Squared Error (MSE) as a Loss Function for Logistic Regression?, published on Towards Data Science, Medium, 2019. Trending in Machine Learning Category. (> 53K views)
  3. Souradip Chakraborty: Dimensionality Reduction in Supervised Framework and Partial Least Square Regression
  4. Souradip Chakraborty An Attempt - Detection of COVID-19 Presence from Chest X-ray Scans Using CNN & Class Activation Maps
  5. Souradip Chakraborty Tutorial on Bayesian Machine Learning