About Me

I recently joined Dolby Laboratories as a Deep Learning Researcher in the Applied AI team in January 2022. Prior to this I graduated with my PhD from the DICE Lab at New York University under the supervision of Dr. Chinmay Hegde, in December 2021. I have also interned at Google in 2021, Adobe in 2020 and MERL in 2018. I am an alumnus of BITS Pilani, Goa, where I earned dual degrees in Physics (M.Sc.) and Electrical and Electronics Engineering (B.E.) in 2015.

My interests lie in the intersection of signal processing, computer vision and deep learning. During the course of my PhD, I worked on several problems in inverse imaging, such as compressed sensing, phase retrieval and HDR imaging using deep neural networks. More recently I have been analyzing unrolled gradient based networks for inverse imaging problems. On the computer vision side, I have worked on developing algorithms to train adversarially robust neural networks. Concurrently I have also looked at new attack models to inspect vulnerabilities of vision based transformer architectures.

Outside of the topics that I explored during my PhD, I am also broadly interested in neural network model compression, designing deep learning based image and video compression models, generative networks and self-supervised learning.

Updates:

March 2022: I will be giving a talk at the SIAM conference on Imaging Science on March 23.

February 2022: Our paper on Inverse Imaging using Generative Priors has been accepted to ICASSP 2022!

January 2022: We have openings in our team, apply here!

January 2022: I moved to the San Francisco Bay Area. Feel free to reach out to me if you’re in the area!