Jenai Xuning Yang

@xuningy

Senior Research Scientist @ NVIDIA | PhD in Robotics @ CMU

Seattle, WA

Joined March 2009

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Jenai Xuning Yang
@xuningy
Apr 20
When every generalist robot model scores 95%+ on a benchmark, the numbers become meaningless. What if we built a photorealistic benchmark that never saturates and can generate new scenes and tasks with AI Workflows in minutes? We introduce RoboLab! 🧵(1/6)
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Jenai Xuning Yang
@xuningy
Aug 25
We released DROID+, a new and improved DROID control stack from SRL. We believe robots (and hardware) should be easy to setup and easy to use, and so we updated the DROID stack to be the same. @HugoHadfield1 github.com/nvlabs/droidpl… Here's pi0.5 doing our "hello world" task:
GIF
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Jenai Xuning Yang
@xuningy
Aug 5
Our team at SRL is hiring! We're looking for people who dive deep, think systematically, and care deeply about doing rigorous work. If you're excited about understanding the science behind building foundation models, please apply!
Elie Aljalbout
@EliJalbout
Aug 5
We're hiring! The Seattle Robotics Lab (SRL) at NVIDIA is hiring a research scientist to work on robot foundation models. The focus will be on investigating the science behind building VLAs, WAMs, and world models for robotics, and leveraging the findings to propose the next
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Jenai Xuning Yang
@xuningy
Jul 12
There's a growing gap between how fast generalist robot policies are improving and how well we can actually evaluate that progress, and understand when and why they fail. I wrote a blog on our take: developer.nvidia.com/blog/how-to-ev… Want to discuss? Find me at #RSS2026!
How to Evaluate General-Purpose Robot Policies for Real-World Deployment | NVIDIA Technical Blog
From developer.nvidia.com
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Jenai Xuning Yang
@xuningy
Jun 15
A fantastic technical deep dive into what's happening now and next in robot foundation models from @moritz_reuss. We're thinking deeply about *how* to build an efficient task generalist policy. Check it out!
Moritz Reuss
@moritz_reuss
Jun 15
World-Action Models (WAMs) have become the second dominant recipe for robot foundation models, next to classical VLAs. So where do they come from, and how do they compare vs VLAs? I wrote an small overview of the WAM landscape, with some personal takes: developer.nvidia.com/blog/pretraine…