People

Jonathan Lorraine is a Senior Research Scientist at NVIDIA, in the Learning and Perception Research (LPR) lab in Toronto. His current work is on agentic AI for science and engineering: agents that propose, run and verify their own experiments, and the measurement discipline that makes their results trustworthy.

His research spans generative models for 3D, video and audio, amortized and bilevel optimization, hyperparameter optimization, and training-data attribution. He is an author of ATT3D and LATTE3D on amortized text-to-3D synthesis, LLaMA-Mesh on 3D mesh generation with language models, Graph Metanetworks, and Score Distillation Sampling for Audio. He previously worked on generative physical AI in NVIDIA's Spatial Intelligence Lab.

He completed his PhD at the University of Toronto in 2024, advised by David Duvenaud, on scalable nested optimization for deep learning.

Homepage: www.jonlorraine.com