Worked on a Humanoid Face Robot project, solving the problem of optimal actuator placement and motor control to enable a Face Robot to enact natural facial movements.

Knight Fellow at the IDeaS Center.

Worked on utilizing Graph based ML techniques such as Graph Neural Networks and Probabilistic Graphical models to learn generalizable physics simulators as well as accelerate the speed of computing simulations.

As part of a research grant from The Bill and Melinda Gates Foundation, I've worked on the development of a non-contact vision based algorithm capable of estimating physiological signals such as heart rate from a diverse adult population.

Led a student team with undergraduate and graduate students to scale the non-contact physiological estimation algorithm to work on mobile platforms such as Android and iOS as well as a web application (https://www.videovitals.org/).

Led a student team to develop a computer vision model that performs human tracking and following. The model was deployed on a commercial drone to use its camera to follow human movement at various speeds.