About
I am a Master’s student in Computer Science at NYU Courant, working on self-supervised representation learning, JEPA-style world models, and machine learning systems that learn useful structure from video, physical simulations, and multimodal scientific data. I previously worked on ADAS and machine learning systems at Robert Bosch India, where I gained experience in perception, autonomous driving, and applied ML research.
Academic Background
Graduate training in computer science with course and research work spanning deep learning, probabilistic models, and scientific machine learning.
Research Motivation
I am motivated by learning systems that extract structure from temporal and multimodal signals with minimal supervision while preserving transfer utility.
Professional Interests
Research engineering, foundational representation learning, and systems that bridge theory, experimentation, and practical deployment.