Summary
Jonathan Lorraine is a research scientist with nine years of AI experience and a recent PhD from the University of Toronto, currently advancing generative AI at NVIDIA’s Toronto Spatial Intelligence lab. He has a strong track record in hyperparameter optimization, nested optimization, and learning in games, with 10+ papers at top ML conferences and over 1,000 citations. Jonathan has translated research into production impact at Google and Meta, notably designing a hyperparameter selection method that cut compute by ~10x while improving deployed model performance. He blends rigorous academic mentorship—years of TA experience and supervising other TAs—with cross-disciplinary collaboration in industry and a boutique hedge fund setting. Passionate about generative modeling and computer vision, he also channels creativity into digital art and hands-on hobbies like gardening and baking, reflecting a practical, experimental mindset.
9 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy (PhD), Computer Science; Machine Learning Group, Doctor of Philosophy (PhD), Computer Science; Machine Learning Group at Department of Computer Science, University of Toronto
Honors Bachelor of Science (HBSc), Mathematics and Computer Science, High Distinction, Honors Bachelor of Science (HBSc), Mathematics and Computer Science, High Distinction at University of Toronto
German, English