Nandita Bhaskhar is a PhD candidate in the Department of Electrical Engineering at Stanford University, advised by Prof. Daniel Rubin. Her research is on developing Robust, Data-efficient and Trustworthy ML for medical applications. More broadly, she is interested robust representational learning, multi-modal foundational models and self-supervision, developing methods for trustworthy ML, active learning and continual learning. Prior to Stanford, she received her Bachelor's degree in Electronics Engineering from the Indian Institute of Information Technology (IIIT) with highest honours. Outside of research, her curiosity lies in a wide gamut of things including but not restricted to biking, social dance, travelling, creative writing, music, getting lost, hiking and exploring new things.

Website: www.stanford.edu/~nanbhas