Jonathan Lorraine

Jonathan Lorraine

I'm a research scientist at NVIDIA in the Spatial Intelligence Lab with Sanja Fidler, working on generative physical AI. I did my PhD in machine learning at the University of Toronto, advised by David Duvenaud. My research centers on ultra-scalable nested optimization - building the tools that power modern AI models, and using them for things like multimodal generation, hyperparameter tuning, and learning in games. Before NVIDIA, I worked on production AutoML at Google and on multi-agent learning at Facebook (Meta) AI Research with Jakob Foerster.

jonlorraine.com · Google Scholar · LinkedIn · @jonLorraine9

Selected work

• OmniDreams - a real-time generative world model for closed-loop autonomous vehicle simulation
• MOTIVE (Oral, ICML 2026) - motion attribution for video generation
• LLaMA-Mesh - unifying 3D mesh generation with language models
• LATTE3D (ECCV 2024) / ATT3D (ICCV 2023) - fast, amortized text-to-3D
• Optimizing Millions of Hyperparameters by Implicit Differentiation (AISTATS 2020)
• Self-Tuning Networks (ICLR 2019) - bilevel optimization of hyperparameters

Research interests

Generative models · bilevel and hyperparameter optimization · meta-learning · multi-agent learning · efficient and multi-fidelity optimization

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