Misc.

Talks and Presentations

• Feb 24 -- [Invited] Talk at the Reinforcement Learning: Recent Trends and Future Challenges Workshop at IISc Bangalore

• 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

Background

• Research Scientist, Amazon Research New York; Supply Chain Optimization Team (SCOT) (worked with Alexander (Sasha) Rakhlin and Dean Foster) (May - Aug 2020)

• Project Associate (with Prof. Aditya Gopalan), Indian Institute of Science (IISc), Bangalore (2015-16)

• Lecturer, PESIT Bangalore (south campus), ECE Dept., Aug 2015 - June 2016

• 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 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.