Presented work at ICML contributed during postdoc at Apple; recognized as an 'Expert Reviewer' for TMLR; paper 'Risk Sensitive Dead-end Indentification in Safety-Critical Offline Reinforcement Learning' accepted for presentation at RLC; successfully defended dissertation.
Research Experience
Senior Research Scientist at MBZUAI, co-leading research efforts into practical usage of reinforcement learning; Postdoctoral Research Scientist within Apple's Special Projects Group in 2024, applying reinforcement learning to high-impact real-world use cases; formerly employed at MIT Lincoln Laboratory.
Education
Graduated in Spring 2024 with a PhD from the University of Toronto and Vector Institute, under Marzyeh Ghassemi; previously completed degrees at Harvard University (working with Finale Doshi-Velez) and Brigham Young University (working with Tadd Truscott).
Background
Senior Research Scientist, focusing on reinforcement learning, machine learning, and causal inference. Aims to develop models and algorithms that enable decision-making under various forms of uncertainty, with the goal of these techniques being adaptable beyond their training domains.
Miscellany
Lived in Sweden and put together a brief guide to Stockholm for colleagues.