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Affiliation: Assistant Professor, Department of CSE, IIT Kanpur, India
Email: sayakrc [at] iitk [dot] ac [dot] in
Research Interests:
Sequential Decision Making: Multi-armed Bandits, Reinforcement Learning
Privacy, Safety, Fairness: Differential Privacy, Algorithmic Fairness
Language Model Optimization: Alignment Algorithms, In-context Learning
About me: I am an Assistant Professor at the Department of Computer Science and Engineering, Indian Institute of Technology Kanpur. Previously, I was a Postdoctoral Researcher at Microsoft Research, India, with Dr. Nagarajan Natarajan. Before that, I was a Postdoctoral fellow at the Department of Systems Engineering, Boston University. Before that, I completed my PhD in the ECE Department of the Indian Institute of Science, Bangalore, where I was advised by Prof. Aditya Gopalan. I have also spent time working at Google in the USA as a research intern. I completed my master's at the Indian Institute of Science, Bangalore, and my bachelor's at Jadavpur University.
Here is my CV (last updated September 2025).
IITK Students interested in working with me: I am currently looking for PhD/Masters/UG students with interests in:
Privacy-Preserving Machine Learning
Sequential Decision Making under Uncertainty
Language Model Optimization
Quantum Machine Learning
Please review my Publications to gain an understanding of my current research. If you are interested, feel free to send an email for further details.
Students looking for short-term projects (less than 3 months): Unfortunately, I don't have any open positions at this time. Please refrain from sending any emails regarding this matter. Most probably, you will not get any reply.
Updates (recent):
September 2025: I have been selected as a Young Associate, Indian National Academy of Engineering (INAE).
June 2025: I am visiting the Department of CSA, IISc Bangalore.
May 2025: I have received a gift fund from Adobe Research.
May 2025: Paper on LLM alignment under preference drift accepted at ICML, 2025.
May 2025: Paper on sample-efficient LLM alignment accepted at ECML-PKDD, 2025.
April 2025: I have received an ANRF early-career research grant. As part of this project, I am seeking one PhD student and one MS student to collaborate with me on privacy-preserving AI algorithms.
March 2025: Invited talk on LLM alignment at REACH Symposium, IIT Kanpur.
December 2024: Invited lecture series on Differential Privacy at Theory CS Winter School 2024, IISc Bangalore.
September 2024: Joined the Department of CSE, IIT Kanpur, as an Assistant Professor.
Representative Publications (see full list here):
Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift. S. Son, W. Bankes, S.R. Chowdhury, B. Paige, I. Bogunovic. International Conference on Machine Learning (ICML), 2025. Link
Communication Efficient, Secure, and Private Multi-Party Deep Learning. Sankha Das, Sayak Ray Chowdhury, Nishanth Chandran, Divya Gupta, Rahul Sharma, Satya Lokam. Proceedings on Privacy Enhancing Technologies Symposium (PETS), 2025. Link
Provably Robust DPO: Aligning Language Models with Noisy Feedback. Sayak Ray Chowdhury, Anush Kini, Nagarajan Natarajan. International Conference on Machine Learning (ICML), 2024. Link
Differentially Private Federated Linear Contextual Bandits. Xingyu Zhou, Sayak Ray Chowdhury. International Conference on Learning Representations (ICLR), 2024. Link
Differentially Private Reward Estimation with Preference Feedback. Sayak Ray Chowdhury, Xingyu Zhou, Nagarajan Natarajan. International Conference on Artificial Intelligence and Statistics (AISTATS), 2024. Link
Bregman Deviations of Generic Exponential Families. Sayak Ray Chowdhury, Patrick Saux, Odalric-Ambrym Maillard, Aditya Gopalan. 36th Annual Conference on Learning Theory (COLT), 2023. Link
Distributed Differential Privacy in Multi-armed Bandits. Sayak Ray Chowdhury, Xingyu Zhou. International Conference on Learning Representations (ICLR), 2023. Link
Shuffle Private Linear Contextual Bandits. Sayak Ray Chowdhury, Xingyu Zhou. International Conference on Machine Learning (ICML), 2022. Link
Bayesian Optimization under Heavy-tailed Payoffs. Sayak Ray Chowdhury, Aditya Gopalan. Neural Information Processing Systems (NeurIPS), 2019. Link
Online Learning in Kernelized Markov Decision Processes. Sayak Ray Chowdhury, Aditya Gopalan. International Conference on Artificial Intelligence and Statistics (AISTATS), 2019. Link
On Kernelized Multi-armed Bandits. Sayak Ray Chowdhury, Aditya Gopalan. International Conference on Machine Learning (ICML), 2017. Link
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