About
I'm a research scientist working on generative AI at NVIDIA's Spatial Intelligence Lab with Sanja Fidler in Toronto. I recently completed my PhD in machine learning, advised by David Duvenaud. My work focuses on ultra-scalable nested optimization, aiming to create and then use the tools powering AI models of the future. For example:
Previously, I worked at Google on their production AutoML pipeline and at Facebook (now Meta) AI Research with Jakob Foerster on multi-agent learning. My M.Sc.A.C. at the University of Toronto was a joint program in Statistics and Computer Science focusing on Data Science, after which I worked at a boutique hedge fund. Even earlier, I did my undergraduate studies with a double major in Computer Science and Mathematics and a minor in Economics, while working with Dmitry Krass on Operations Research.Potential Interns: Students seeking an internship at NVIDIA's Spatial Intelligence Lab should look for more information on our webpage. See this link for open positions, or contact members with relevant interests for more details.
E-mail: lorraine@cs.toronto.edu
Location: Toronto, Canada
Papers
Teaching
- CSC2547: Automated Reasoning with Machine Learning (Winter 2023)
- CSC2626: Imitation Learning for Robotics (Fall 2022)
- CSC401/CSC2511: Natural Language Computing (Winter 2022)
- CSC2516: Neural Networks and Deep Learning (Winter 2021)
- CSC2515: Machine Learning (Winter 2021)
- CSC311: Introduction to Machine Learning (Fall 2020)
- CSC413: Neural Networks and Deep Learning (Winter 2020)
- CSC2547: Learning to Search (Fall 2019)
- CSC412: Probabilistic Learning and Reasoning (Winter 2019)
- CSC411: Introduction to Machine Learning (Fall 2018)
Other Links
- Google Scholar
- Twitter / X
- GitHub
- YouTube
- ArXiv
- OpenReview
- ORCID
- DBLP
- Semantic Scholar
- ResearchGate