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 the 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 focused on Data Science, after which I joined a boutique hedge fund. Even earlier, my undergraduate studies included 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 information on our webpage. See this link for open positions, or contact members with relevant interests for 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