I am a doctoral fellow within the Max Planck ETH Center for Learning Systems, where I am advised by Thomas Hofmann at ETH Zürich (home base) and Bernhard Schölkopf at MPI-IS Tübingen. My research interests are in the broad areas of deep learning theory, optimization, and causal representation learning.
Previously, I finished my Master’s degree in Data Science at EPFL, where I worked on model fusion and natural language processing via optimal transport, advised by Martin Jaggi. I did my master thesis at IST Austria with Dan Alistarh and focussed on efficient second-order approximation for compressing neural networks. Before EPFL, I completed my undergraduate studies in Computer Science at Indian Institute of Technology (IIT) Roorkee.
For more details on my research, check out this (now old) research statement.
Ph.D. in Computer Science, 2024
ETH Zürich, Max Planck Institute for Intelligent Systems
M.Sc. in Data Science, 2020
Ecole Polytechnique Federale de Lausanne
B.Tech in Computer Science, 2017
Indian Institute of Technology, Roorkee
Disclaimer: The ‘2020 Reflection(s)’ refer to only my own personal views! (also, serves as an amusement)