I am a PhD candidate working on Machine Learning, in the Department of Electrical & Computer Engineering, at the University of Illinois at Urbana-Champaign (UIUC). I am advised by Sewoong Oh from the School of Computer Science & Engineering in the University of Washington (UW), Seattle. I also closely collaborate with Prateek Jain and Praneeth Netrapalli from Google Research (previously Microsoft Research), and Niao He from ETH Zurich.
Previously, I received my Master of Science degree in Electrical & Computer Engineering from UIUC, and my Bachelor of Technology (Honors) degree in Electrical Engineering along with a minor in Operations Research from Indian Institute of Technology Madras (IIT-M), India.
Research (List of Publications & Google Scholar profile)
I am interested in optimization and statistical methods for machine learning. Currently, I study large-scale first-order optimization methods and deep generative models. During my masters and bachelors, I worked on collaborative preference ranking using partially observed data and online resource allocation in wireless communication.
Internship Experience
• May 2017 - Aug 2018: At Google: Cloud AI, Sunnyvale, with Li-Jia Li and Chong Wang
• Summer 2016: At Google: Research and Machine Intelligence, Mountain View, with Raghunandan Keshavan
• Summer 2013: At TU Dresden, Germany with Prof. Dr.-Ing. Eduard A. Jorswieck
Recent news
• Dec 2020: Giving a Spotlight talk on constrained optimization at NeurIPS 2020!
• Nov 2020: Will present Frank-Wolfe methods for stochastic regret minimization at Optimization at Machine Learning workshop at NeurIPS 2020!
• Sep 2020: Paper on projection-efficient optimization and non-smooth Frank-Wolfe method got accepted into the Spotlight sessions at NeurIPS 2020 conference!
• Jun 2020: Paper on learning disentangled representation using Generative Adversarial Networks (GANs) got accepted into ICML 2020 conference!