Judy Hoffman

@judyfhoffman

Associate Professor @UCIrvine, formerly @GeorgiaTech. Researcher in Computer Vision, Machine Learning, AI. PhD from @berkeley_ai. Views my own.

jhoffman.github.io

Joined November 2014

Judy Hoffman
@judyfhoffman
Mar 24
A monumental effort that would not have been possible without @simar_kareer and @ryan_punamiya's leadership! Excited to see how this project grows 📈
Simar Kareer
@simar_kareer
Mar 23
We've wanted to study human to robot transfer at scale, but the right dataset was missing. Introducing EgoVerse! - EgoVerse is about quantity and quality. The data is vast and directly usable - EgoVerse is growing. We're excited to onboard labs and startups, reach out!
Judy Hoffman
@judyfhoffman
Mar 24
Excited about the release of EgoVerse and looking forward to seeing what data the community will contribute! Now people can teach robots by passively collecting data as we move about the world. An important step towards scaling demonstration data! 🤖
Danfei Xu
@danfei_xu
Mar 23
Introducing EgoVerse: an ecosystem for robot learning from egocentric human data. Built and tested by 4 research labs + 3 industry partners, EgoVerse enables both science and scaling 1300+ hrs, 240 scenes, 2000+ tasks, and growing Dataset design, findings, and ecosystem 🧵
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Judy Hoffman
@judyfhoffman
Jan 22
Congratulations to @ryan_punamiya and @danfei_xu on this amazing accomplishment!! It's been a pleasure working together.
Danfei Xu
@danfei_xu
Jan 21
Proud advisor moment: Congrats to @ryan_punamiya for winning the Runner-Up (2nd place) of the prestigious CRA Undergraduate Research Award! cra.org/about/awards/o…
Judy Hoffman
@judyfhoffman
Sep 25, 2025
EgoBridge (NeurIPS'25) makes human data more useful for training robot policies. We show that the robot can even learn to operate in scenes only shown from the human view. Check out this thread from lead author @ryan_punamiya -- he's applying for PhD programs this cycle!
Ryan Punamiya
@ryan_punamiya
Sep 25, 2025
Robots struggle to learn new skills from human videos. Why? We found that naive co-training produces disjoint distributions. Our EgoBridge (NeurIPS’25) extends Optimal Transport to align human-robot latents, improving success by 44% and generalization to human-only tasks!🧵
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Judy Hoffman
@judyfhoffman
Mar 27, 2025
🚀 Excited about how generative AI can power experimental (not just observational) audits of ML systems that reveal actionable insights into performance and bias? Join us at EMACS (Experimental Model Auditing with Controllable Synthesis) workshop @CVPR!
sites.google.com
EMACS CVPR 2025
This workshop focuses on generative techniques for experimental auditing of machine learning models, to analyze performance, bias, and failure modes