I am currently a Data Scientist III at S&P Global.
My research interests lie in Efficient Learning, with a focus on developing computationally efficient methods for adapting and optimizing modern machine learning models.
I completed my Master’s degree at IIIT Delhi, where I was advised by Prof. Saket Anand. Prior to that, I completed my B.Tech. from NIT Nagpur, where my bachelor’s thesis was advised by Prof. Pradip B. Damole.
Broadly, I am interested in efficient model adaptation, optimization, representation learning, and evaluation. I am particularly interested in methods that improve modern machine learning systems while considering computational cost, reliability, and practical usability.
A list of my papers is online, together with my CV and additional writing. Please feel free to get in touch.
News
- Self-Routed Tensor Adapters for Parameter-Efficient Universal Visual Adaptation has been accepted to the ECCV Workshop · Archival Track.