Stewart Jamieson

I’m an AI researcher and technical leader working on risk-aware, uncertainty-aware machine learning — AI systems that understand the limits of their own knowledge and act safely because of it. As President of Themis AI— an MIT CSAIL spinoff founded by Alexander Amini, Daniela Rus, and Elaheh Ahmadi — I lead the company’s technical strategy and the research and product teams building the decision layer for AI: a platform that estimates the risk behind each prediction and proposed action, so organizations can automate what AI handles reliably and focus expert review where it matters.

This work is the direct continuation of a decade-long research thread. My undergraduate thesis at the University of Toronto applied uncertainty quantification to make autonomous-driving vision safer. My doctoral research in the MIT–WHOI Joint Program — co-supervised by Prof. Jonathan How (MIT) and Dr. Yogesh Girdhar (WHOI) — developed risk-aware online learning and Bayesian methods that let autonomous robots reason about the value of information: deciding what is worth learning, communicating, and acting on when operating in unfamiliar, bandwidth-limited environments like the deep sea.

Along the way I’ve been fortunate to have that work recognized — a Best Paper Award at ICRA 2020, and a 2024 article in the journal Artificial Intelligence on finding optimal exploration–exploitation trade-offs through Bayesian risk minimization. Today I’m focused on turning those ideas into AI that organizations can depend on to make the right decisions under uncertainty.