About
I am a PhD graduate from the Robotics Institute at the University of Michigan. I was a member of ROAHM Lab supervised by Prof. Ram Vasudevan. I hold a Bachelors degree in Mechanical Engineering from McGill University and a Masters degree in Robotics, Systems and Control from ETH Zurich.
My research focuses primarily on multi-modal semantic mapping for robotics using probability theory and functional analysis. By treating neural network outputs as measurements, I use probability theory and Bayes’ Theorem to fuse these measurements together and quantiy the uncertainty of the network outputs across time. I am also interested in leveraging Riemannian geometric priors for learning as reasoning about these Riemanninan embedding spaces for robot task planning.