I am the Chief Scientist at Inverted AI where I lead a team of researchers working on the development human like multi-agent behavioral models for realistic self-driving car simulation and score based generative models. Before my position as Chief Scientist I worked at Inverted AI as a research scientist, focusing on multi-object tracking and traffic scene generation. Before starting at Inverted AI I was a postdoc working in the UBC computer science department with Frank Wood, and in the UBC statistics department with Trevor Campbell. My work was on developing and applying permutation invariant models with a tractable probability density. I was also part of a project that applies techniques of probabilistic programming for the purpose inverting physical models, with the use of neural surrogates. During this period I was part of the DSI-CRN collaboration, which aims to leverage machine learning methods to develop better composite materials.

Before starting as a machine learning researcher, I did a PhD in condensed matter physics at UBC in the group of Andrea Damascelli. My research focused on understanding the interplay between spin-orbit coupling and electron-electron interactions. Before that, was a MSc student in Amsterdam, working with Mark Golden, understanding the effects of light on the energy states of topological insulators.