June 2020 Our latest work on dynamically-feasible trajectory forecasting from heterogeneous data, Trajectron++, was accepted to ECCV 2020! Further, a paper combining Trajectron++ with a downstream risk-sensitive controller was accepted to IROS 2020! See you online!
June 2020 Wrote a blog post about trajectory forecasting for the Stanford AI Lab Blog!

About Me

I am an electrical and computer engineer turned computer scientist turned roboticist pursuing a PhD in aeronautics and astronautics under the supervision of Professor Marco Pavone in the Autonomous Systems Lab.

I obtained a Master's in Computer Science from Stanford University in 2018, specializing in Artificial Intelligence (AI). Prior to that, I obtained a Bachelor of Applied Science with High Honours in 2016 from the University of Toronto's rigorous Engineering Science program, majoring in Electrical and Computer Engineering with a Robotics/Mechatronics minor.

Resume/CV (updated July 4, 2020)