Changan Chen @changanvr
Co-founder and Chief Research Officer @RhodaAI Scaling visual intelligence toward physical AGI. Prev: @Stanford @UTAustin @FAIR. changan.io Bay Area, San Francisco Joined December 2015-
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I am thrilled to join rhoda.ai @RhodaAI as an advisor, where I am helping harness the abilities of large-scale pre-training and video models for robotics, putting many of my lab's research learnings of the past few years into practice! I will be in-person at the Mountain View office for part of the summer - reach out if you want to chat :)
@vincesitzmann @RhodaAI Welcome to Rhoda! Very excited to work with you!
Huge shoutout to the Rhoda team for making the event happen! 🙌 If you’re at @CVPR, come say hi: @ericryanchan @alexwbergman @isskoro @leooeld @QianqianWang5 @GordonWetzstein @vincesitzmann @BaadeAlan We’re hiring! 🚀 Careers: rhoda.ai/careers
One theme came up over and over in the past few days: excitement around world models for robotics. 🤖 The interest from the research community has been incredible. It feels like we’re entering a new phase for physical AI by approaching it with real time video models!
I’ve known Yuejiang and worked with him for many years. He’s always curious, humble, and eager to learn new things. He's not only a fantastic researcher but also one of the best mentors I've worked with. If you're pursuing a PhD in embodied AI, consider applying to his lab!
Excited to share that I’ll join @NUSComputing as an Assistant Professor in 2027 🏛️ I’ll build LEMA Lab: lema-nus.github.io, study the principles of embodied intelligence, & empower every lab member to thrive 📢 Recruiting 3-6 PhD students in the next application cycles
We’re hiring across research and engineering 🚀 Open roles: • video model pre-training • robot post-training • ml infrastructure • deployment • phd internships Careers: rhoda.ai/careers
I'll be at CVPR next week (6/3–6/7). If you’re working on or exploring opportunities in video models for robotics (research or engineering), happy to chat 🤖 We’re also hosting a Rhoda party Thursday night with many of our technical team in town. DM me for an invite 🍻
We got our large-scale foundational video model running real-time on an edge device! Amazing work led by @leooeld!
Can a large foundation video model run as a real-time robot policy at the edge, on a single RTX 5090? • ✅ No quantization • ✅ No distillation • ✅ Full denoising (all the way from noise to clean video) We just proved it's possible. 👇🎬
@RhodaAI Learning from human demonstrations is a crucial step toward enabling robots to quickly acquire new tasks without relying on teleoperation.
@GeneralistAI @BerkayAntmen @RhodaAI Great to see the shell game getting traction! Long-context memory is genuinely hard to get right. Good to see the robot learning field paying more attention to long-context visual memory.
Amazing work on long-context video memory and reasoning led by @QianqianWang5!
Here’s something we’ve never seen done before. Real-world tasks are long and ambiguous. Solving them requires visual memory and state tracking. Most robot policies only see the last few frames. Ours doesn't. We put our DVA, FutureVision, to the perfect testbed: the shell game
@rhodaai While this may seem like a simple task, it requires long-context memory and the ability to reason about object motion across an entire sequence. This capability is naturally supported by our video models that are trained on large-scale video data.
We are entering a new era of robot deployment. With our model, teams can iterate on solutions and data collection more rapidly thanks to highly efficient training. What once took months can now be achieved in as little as 19 days, bringing development to an entirely new pace.
1/ We are speed running industrial robotics. It took us just 19 days from the first day of data collection to filming a 2.5-hour continuous run of our model autonomously breaking down industrial containers — zero human intervention. The data efficiency of our DVA model is
@karpathy This is cool! I wonder what you think about the following potential issues: 1. How does the agent avoid getting stuck in local minima during exploration? 2. How well does training on a small model translate to larger-scale models with significantly more compute and data?
Yuke Zhu @yukez
23K Followers 477 Following Associate Professor @UTCompSci | Director @NVIDIAAI Co-Leading GEAR | CS PhD @Stanford | Building generalist robot autonomy in the wild | Opinions are my own
Huihan Liu @huihan_liu
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Jonathan Le Roux @JonathanLeRoux
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Guanya Shi @GuanyaShi
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Chenggong "Alex" Zhan... @ChenggongAlex
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Yuke Zhu @yukez
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Sander Dieleman @sedielem
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Yuandong Tian @tydsh
47K Followers 950 Following Co-founder of @Recursive_SI. ex-Meta FAIR Director. ex-Google. Reasoning, Optimization and Understanding LLM. Novelist in spare time. PhD in @CMU_Robotics.
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9K Followers 812 Following Teaching multimodality to Gemini, Nano Banana, and more @GoogleDeepMind. PhD from @ETH and @MPI_IS.
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29 Followers 337 Following AI+ Mental Health + BCI | Prev. PhD in ML @GeorgiaTech (computational neuropsychiatry), @meta @calico @thetawellnessai
Adam Patni @adam_patni
674 Followers 842 Following programming robots @RhodaAI ex-@sauronsystems, @spacex, @wayve_ai, @georgiatech
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193 Followers 57 Following Co-Founder & Chief Product Officer @ Rhoda AI
Alex Bergman @alexwbergman
504 Followers 172 Following building something new @rhoda_ai_. ex CTO / Co-founder @hedra_labs | ex @stanford PhD
Tongzhou Mu 🤖🦾�... @tongzhou_mu
3K Followers 988 Following Scaling video world models for robots @RhodaAI | Built 1st version of ManiSkill https://t.co/NuQOXaNhud | Prev @UCSanDiego @1x_tech @NVIDIA @MSFTResearch
Joanne Truong @joannetruong
665 Followers 221 Following Research Scientist @ Rhoda AI. Prev: RS @MetaAI, PhD @GeorgiaTech
ali @aliteracy
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Jiaxun Cui 🐿️ @cuijiaxun
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Xun Huang @xxunhuang
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Generalist @GeneralistAI
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