Biography

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.

• Yay, 2 papers at NeurIPS 2020 (Model Fusion; WoodFisher)! :D
• Gave a talk on Model Fusion at the DLCT reading group (slides).
• Invited talk at the Google sparsity reading group on WoodFisher (slides).
• Top 33% reviewer, certificate of appreciation ICML 2020.
• September 1st, 2020: Moved to Zürich for my PhD! :)
• Presented Context Mover’s Distance (CMD) at AISTATS 2020 (video).
• Participated in the Cornell, Maryland, Max Planck pre-doctoral research school 2020.
• The preprint based on my master thesis is online, WoodFisher: Efficient second-order approximations for model compression.
• Selected to attend the Heidelberg Laureate Forum that will happen next year (amongst one of 225 young researchers in Maths and CS worldwide).
• Our Context Mover’s Distance paper is accepted at AISTATS 2020.
• Presented our work on Model Fusion via Optimal Transport at the OTML workshop in NeurIPS (2019).
• Received travel award & selected amongst top 50% reviewers, NeurIPS (2019).
• Our paper on Context Mover’s Distance & Barycenters is accepted at ICLR DeepGenStruct workshop (2019).
• Preprint of my internship work at FAIR is out, GLOSS: Generative Latent Optimization of Sentence Representations (2019).
• Preprint for our recent paper on Wasserstein is all you need (2018).
• Student grant to attend ML4P workshop in Oxford (2018).
• Excited to join Facebook AI Research (FAIR) as an intern this fall (2018).
• Selected for The Alan Turing Institute’s, data study group (2017).
• Offered fulltime Research Fellow position at Microsoft Research India (2017).
• Received Honda Y-E-S (Young Engineers and Scientists) Award 2016 (one of 14 students selected all over India).
• Awarded Google Venkat Panchapakesan Scholarship and invited visit to Google YouTube and Mountain View offices (2016).