My research focuses on developing machine learning methods grounded in geometry and physics, with applications in scientific computing, dynamical systems, and robotics.
I am an Assistant Professor in the Department of Mechanical and Aerospace Engineering, Center for Statistics and Machine Learning at Princeton University, and Robotics at Princeton. I hold an associated faculty position with Computer Science and the Princeton Plasma Physics Lab
Prior to my current appointment, I was part of the inaugural class of Princeton Presidential Postdoctoral Fellows and mentored by Naomi Leonard. I completed my PhD in Computer Science and Master’s in Robotics at the University of Pennsylvania where I was supervised by Kostas Daniilidis. Prior to my graduate work, I completed Bachelor’s degrees in Mechanical Engineering and Computer Engineering at San Jose State University.
Graduate Students
My research interests mainly lie on AI4Sci and Engineering problems.
I’m broadly interested in integrating machine learning with numerical PDE solvers to develop more efficient and adaptive algorithms.
My current research focuses on developing interpretable deep graph neural networks with opinion dynamics.
My research interests are leveraging deep learning to understand and control dynamical systems.
My research interests lie at the intersection of robotics, machine learning, and physics-informed geometric methods.
My primary research interests lie at the intersection of robotics, computer vision, and machine learning.