Feb 25 -- [Invited Talk] Presented works on Non-Convex Optimization in the Probability Seminar, School of Mathematics, University of Bristol
Jan 25 -- [Invited Talk] At Reinforcement Learning Workshop 2025, IISc Bangalore on Multi-Agent Multi-armed Bandits (see video; starts at 1:42:00)
Dec 24 -- [Invited Talk] New Challenges in Federated Learning; IISA 2024, CUSAT
July 24 -- Poster presentation on Agnostic AM and EM algorithms, ICML 2024, Vienna
July 24 -- Poster presentation on Causal Inference, ICML 2024, Vienna
July 24 -- Presented paper on Markets and Bandits, ISIT 2024, Athens
July 24 -- Presented paper on Distributed Cubic Newton, ISIT 2024, Athens
July 24 -- Presented paper on Adversarial attacks on CPS, ISIT 2024, Athens
Feb 24 -- [Invited] Talk at the Reinforcement Learning Workshop at IISc Bangalore on Dynamic Matching Markets (see video; starts at 1:03:00)
Feb 24 -- [Invited] Competing Bandits in Non Stationary Matching Markets, TIFR Mumbai
Mar 23 -- Large Scale Non-convex Optimization--Provable guarantees and convergence rates, Dept of Computer Science and Engg, IIT Bombay
Feb 23 -- [Invited Talk] Federated Learning -- Challenges and Algorithms, Dept. of Electrical Engg, IIT Bombay
Sept 22 -- Presented Model Selection in Reinforcement Learning paper at ECML-PKDD 2022
Presented Collaborative Multi-agent Bandits paper at ECML-PKDD 2022
July 22 -- Presented Spotlight talk at ICML 2022, Baltimore on our learning with mixture of regression work
July 22 -- Presented Spotlight talk at ICML 2022, Baltimore on our contextual linear bandit work
May 2022 -- Decentralized Competing Bandits In Non-Stationary Matching Markets; Information Theory and Application (ITA), 2022
Jan 2022 -- Federated Learning; Communication Efficiency and Robustness; The Institute for Learning-enabled Optimization at Scale, (TILOS-AI Institute).
Dec 2021 -- Challenges in large scale Federated Learning; TRIPODS faculty meet, UC San Diego
Oct 2021 -- Large Scale learning in Bandits and RL-- SysCon, IIT Bombay
July 2021 -- LocalNewton: Reducing Communication Rounds for Distributed Learning -- Uncertainty in Artificial Intelligence (UAI)
April 2021 -- Distributed Newton Can Communicate Less and Resist Byzantine Workers -- NSF-TRIPODS Workshop on Communication Efficient Distributed Optimization
April 2021-- Escaping Saddle Points in Distributed Newton's Method with Communication efficiency and Byzantine Resilience -- NSF-TRIPODS Workshop on Communication Efficient Distributed Optimization
Nov 2020 -- Invited talk at Electrical Engg. Dept, IIT Delhi on Statistics, Computation and Adaptive aspects of offline and online learning.
Oct 2020 -- Computer Science and Automation (CSA), Indian Institute of Science (IISc), Bangalore on Statistics, Computation and Adaptive aspects of offline and online learning.
Sept 2020 -- Alternating Minimization converges super-linearly for mixed linear regression --- AISTATS 2020
Sept 2020 -- Model Selection for Finite and Continuous-Armed Stochastic Contextual Bandits --- ICML Workshop on Theoretical Foundations of Reinforcement Learning and Privacy, 2020
July 2020 -- An Efficient Framework for Clustered Federated Learning --- ICML Workshop on Federated Learning and Privacy, 2020
June 2020 -- Max-affine Regression with Universal Parameter Estimation for Small-ball Designs --- ISIT, 2020
June 2020 -- Some Performance Guarantees of Global LASSO with Local Assumptions for Convolutional Sparse Design Matrices --- ISIT, 2020
June 2020 -- Communication-Efficient Byzantine-Robust Distributed Learning --- Information theory and applications (ITA), 2020
Dec 2019 -- Max affine regression: algorithm and analysis --- IND-STATS (Innovations in Data and Statistical Sciences), 2019
July 2019 -- Alternating Minimization for Max-Affine Regression -- Signal Processing with Adaptive Sparse Structured Representations (SPARS), 2019
July 2019 -- Robust Heterogeneous Federated Learning --- ICML Workshop on Privacy and Security in ML, 2019
Oct 2018 -- Online Scoring with Delayed Information: A Convex Optimization Viewpoint --- Allerton 2018
Oct 2018 -- Faster Data-access in Large-scale Systems: Network-scale Latency Analysis under General Service-time Distributions --- Allerton 2018
Bio
Assistant Professor, Centre for Systems and Control Engineering (SysCon), IIT Bombay, 2022 Dec - 2024 Dec
Postdoc at UC SanDiego 2021 June - 2022 Dec
Research Scientist, Amazon Research New York; Supply Chain Optimization Team (SCOT), May - Aug 2020
PhD, UC Berkeley 2016 Aug - 2021 May
Project Associate (with Prof. Aditya Gopalan), Indian Institute of Science (IISc), Bangalore (2015-16)
Networking Engineer, Cisco Systems India Pvt. Ltd. (2014-15).
Masters in Engineering (M.E) in Electrical Communication Engineering, IISc Bangalore (2012-2014).
Internship at Indian Statistical Institute (ISI), Kolkata (May - Aug, 2011).
Bachelors in Electronics and Telecommunication Engineering, Jadavpur University (2008-2012).
Accolades:
Recepient of Amazon-IITB AI-ML initiative award, 2024
Recepient of Amazon-IITB AI-ML initiative inaugural award, 2023
HDSI (Data Science) Postdoctoral Fellowship from UC San Diego
Departmental Fellowship, EECS, UC Berkeley for Spring 2020
Excellence Award from EECS Department, UC Berkeley, 2016
Graduate Fellowship for the year 2016-17, EECS Dept, UC Berkeley
All India Rank 37 in GATE-2011 (EC) (Among approximately 1,37,000 candidates)
Recipient of Gold & Bronze Medals from Jadavpur University, Kolkata for scoring highest aggregate marks in all theoretical subjects in ETCE Department and for securing 2nd position in the entire faculty of Engineering respectively.
Ranked 38 in West Bengal Joint Entrance Examination, 2008 (Engineering) (Among approximately 80000 candidates).
Ministry of Human Resource Development (MHRD) Scholarship for University Students Awardee for performance in Higher Secondary Education,2008, West Bengal, India.