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Achievements

Achievement: Pull Sharkx4Achievement: Pair Extraordinairex4Achievement: Galaxy Brainx4Achievement: Public SponsorAchievement: YOLOAchievement: QuickdrawAchievement: Arctic Code Vault ContributorAchievement: Starstruck

Achievements

Achievement: Pull Sharkx4Achievement: Pair Extraordinairex4Achievement: Galaxy Brainx4Achievement: Public SponsorAchievement: YOLOAchievement: QuickdrawAchievement: Arctic Code Vault ContributorAchievement: Starstruck

Highlights

Organizations

@NVIDIA @VectorInstitute @nv-tlabs

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lorraine2/README.md

Jonathan Lorraine

I'm a Senior Research Scientist at NVIDIA Research in Jan Kautz's Learning and Perception Research (LPR) group, working on agentic AI for science and engineering. My research spans rewards, verifiers, and evaluation for self-improving systems; world models and generative models for 3D and video; and scalable nested optimization. I completed my PhD in machine learning at the University of Toronto, advised by David Duvenaud. Before NVIDIA, I worked at Google and Meta AI.

jonlorraine.com · Google Scholar · NVIDIA Research · OpenReview · ORCID · Hugging Face · LinkedIn · @jonLorraine9

Selected work

Research interests

Agentic AI for science and engineering · World models · Generative models · Evaluation and verifiers · Nested and bilevel optimization

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  1. nv-tlabs/LLaMA-Mesh nv-tlabs/LLaMA-Mesh Public

    Unifying 3D Mesh Generation with Language Models

    Python 1.2k 77

  2. nv-tlabs/omni-dreams nv-tlabs/omni-dreams Public

    NVIDIA Cosmos-Dreams (fka NVIDIA OmniDreams) is a world model that generates photorealistic video for autonomous-driving simulation in real time.

    Python 314 23

  3. asteroidhouse/self-tuning-networks asteroidhouse/self-tuning-networks Public

    Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088

    Python 62 14

  4. hypernet-hypertraining hypernet-hypertraining Public

    Code for Stochastic Hyperparameter Optimization through Hypernetworks

    TeX 29 10