Neha Mukund Kalibhat

I am a Computer Science PhD student at the University of Maryland, College Park. I am advised by Prof. Soheil Feizi and I work in the Center for Machine Learning lab. My research interests span various deep learning approaches including self-supervised representation learning, generative models (GANs, VAEs and Flows) and lottery tickets.

I interned at Meta AI in 2021 with the AI Integrity research group where I worked on understanding the flexibility and failure modes of self-supervised representations. Before UMD, I worked at Citrix for over 2.5 years on email intelligence, analytics and iOS app development. I received my bachelors degree in Computer Science from PES University in 2017 where I did undergraduate research in the intersection of machine learning and high-performance computing.





Google Scholar



Understanding Representation Quality in Self-Supervised Models

Neha Mukund Kalibhat, Kanika Narang, Hamed Firooz, Maziar Sanjabi, Soheil Feizi

Under Review, [Paper]

Multi-Domain Self-Supervised Learning

Neha Mukund Kalibhat, Yogesh Balaji, Bayan C. Bruss, Soheil Feizi

Under Review, [Paper]

Understanding Over-parameterization in Generative Adversarial Networks

Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi

ICLR 2021, [Paper]

Winning Lottery Tickets in Deep Generative Models

Neha Mukund Kalibhat, Yogesh Balaji, Soheil Feizi

AAAI 2021, [Paper]

Software Troubleshooting using Machine Learning

Neha M. Kalibhat, Shreya Varshini, Chid Kollengode, Dinkar Sitaram, Subramaniam Kalambur

HiPC 2017, [Paper]