I hold an MS in Computer Science from the University of Southern California (USC). Before my time at USC, I worked as a Software Developer at Morgan Stanley. I graduated from the Indian Institute of Technology (IIT) Guwahati with a B.Tech in Engineering Physics and a minor in Computer Science and Engineering.
I am currently looking for research positions in robotics.
Research interests
I am primarily interested in exploring data-driven approaches to solve challenges in robotics. Classical control theory offers safety and interpretability and is grounded in real-world abstractions. On the other hand, learning-based methods are powerful function approximators and are a viable alternative when analytical solutions are infeasible due to complexity or computational intractability. I wish to combine these approaches to build efficient, safe, and robust algorithms for robotic control, targeted toward the agile locomotion of legged robots.
Motivated by the broad applications of manipulation, another direction that I’m interested in is representation learning and planning for dexterous manipulation in contact-rich environments. I’m eager to explore how we can simplify planning by learning task-specific representations, targeted towards applications in medicine and agriculture. In all my endeavors, I aim to incorporate first principles-based inductive biases across the entire computational framework, from representation to controls.