Xingyu Lin

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Xingyu Lin

Xingyu Lin

@Xingyu2017

Robot learning @openai. Previously @berkeley_ai @SCSatCMU. #Learning #Robotics

Berkeley, CA Katılım Mart 2017
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Xingyu Lin
Xingyu Lin@Xingyu2017·
What state representation should robots have? 🤖 I’m thrilled to present an Any-point Trajectory Model (ATM), which models physical motions from videos without additional assumptions and shows significant positive transfer from cross-embodiment human and robot videos! 🧵👇
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Pengchuan Zhang
Pengchuan Zhang@PengchuanZ·
I’m joining OpenAI to work on World Simulation and Robotics, after 3.75 years at FAIR working on SAM and Llama. I’m thrilled to explore how visual perception, world model and robotics can come together to build physical intelligence.
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Danijar Hafner
Danijar Hafner@danijarh·
Today is my last day at @GoogleDeepMind. After almost exactly 10 years at Google including 12 internships and the last 2 1/2 years full time, it really feels like a chapter coming to an end. I'm grateful for all the experiences and friends I've made at Google and DeepMind. I still remember my first Brain internship in Mountain View in 2016 with James Davidson and @V_Vanhoucke, at a time where nobody had a working PPO implementation and we were wrangling with TensorFlow graphs 😄 The moment @lukaszkaiser showed us the first plausible Wikipedia page generated by a "big" LSTM. @ashVaswani full of excitement explaining the compute efficiency of a new architecture that later became the Transformer and asking me to try it for RL (I did not :P) The excitement to work on Deep RL and generative models at DeepMind during my master's in London, which turned into PlaNet with @countzerozzz and @itfische. Figuring out Karl Friston's free energy principle with Nicolas Heess and @AdaptiveAgents (which took a few more years to get right). Spending a good part of my PhD at the Brain Team in Toronto working on multiple generations of Dreamer with @mo_norouzi, various collaborations, and celebrating the Turing Award with @geoffreyhinton. And over the last few years working from Berkeley/SF on world models with @wilson1yan with significant resources thanks to @countzerozzz and @koraykv, and seeing video models & world models accomplish results that seemed completely out of reach just a few years ago. With mixed feelings but also excitement, it's time to start a new chapter!
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Mostafa Rohaninejad
Mostafa Rohaninejad@MostafaRohani·
1/n I’m really excited to share that our @OpenAI reasoning system got a perfect score of 12/12 during the 2025 ICPC World Finals, the premier collegiate programming competition where top university teams from around the world solve complex algorithmic problems. This would have placed it first among all human participants. 🥇🥇
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Xingyu Lin
Xingyu Lin@Xingyu2017·
It's increasingly evident that synthetic data—including simulation—will be essential for training reliable robotic skills. Big kudos to the Genesis team for pushing the frontier!
Genesis AI@gs_ai_

Today, We’re launching Genesis AI — a global physical AI lab and full-stack robotics company — to build generalist robots and unlock unlimited physical labor. We’re backed by $105M in seed funding from @EclipseVentures, @khoslaventures, @Bpifrance, HSG, and visionaries including @ericschmidt and @Xavier75 . General-purpose robots will be the next chapter in human history. Half of global GDP is physical. Less than 5% is automated. Today’s robots are too narrow, rigid, and expensive to scale. We need a new generation of adaptable, foundation-model-driven systems. We are a new generation of robotics builders, united by a shared mission to push the boundaries of physical AI. Our team brings together the minds behind many recent key advances spanning robotics, imitation learning, RL, simulation, GPU compilers, and foundation models — bridging historically siloed communities. We co-created UMI and Diffusion Policy, pioneered RL for superhuman drone racing, and scaled robotic data pipelines at NVIDIA GR00T. We introduced the paradigm of generative simulation, built Genesis, Jiminy, Flightmare, and GVBD Voxels, and invented the IPC algorithm. We built cross-platform GPU compilers VeriGPU, DeepCL, Coriander, and the original PyTorch, and industry-leading rendering engines at Epic, Unity, and Google. We also spearheaded the first multimodal foundation models at Mistral AI and Apple Intelligence. Now, we’ve come together at Genesis AI to close the loop, and build what’s next. Join us → genesis-ai.company/join-us

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Chuang Gan
Chuang Gan@gan_chuang·
World Simulator, reimagined — now alive with humans, robots, and their vibrant society unfolding in 3D real-world geospatial scenes across the globe! 🚀 One day soon, humans and robots will co-exist in the same world. To prepare, we must address: 1️⃣ How can robots cooperate or compete intelligently? 2️⃣ How do humans build social bonds and communities? 3️⃣ How can both co-exist in an open, dynamic world? Announcing Virtual Community Project — a social-physical world simulator, where human characters and robotic agents can interact, grow, and co-evolve within open-world societies, stretching from London to New York, and beyond! Key features include: ✅ Unified multi-agent physics simulations for rich social + physical interactions of humans and robots ✅ Massive auto-generated 3D scenes grounded with the rea-world geospatial data ✅ Agent communities populated by robots and LLM-driven human characters with rich appearances, personalities, and social ties. 🌍 Enter our Virtual Community, an open world to study embodied AI at scale— one social-physical world model at a time! 🔗 Project: virtual-community-ai.github.io 💻 Code: github.com/UMass-Embodied… Paper: virtual-community-ai.github.io/paper.pdf 1/n
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Jeremy Collins
Jeremy Collins@jerthesquare_·
@Xingyu2017 Looking forward to seeing you there, Xingyu! Would love to chat about learning from videos sometime soon.
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Xingyu Lin
Xingyu Lin@Xingyu2017·
Traveling to #RSS2025 next week. Looking forward to meeting everyone, and chatting about humanoid robots!
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Philipp Wu
Philipp Wu@philippswu·
Very excited to to have ROS integration for GELLO, built by Franka Robotics! Robot teleoperation data is becoming more and more important for large scale Robot foundation model training. Great to see larger adaption for low cost, scalable teleoperation!
FRANKA ROBOTICS@FRANKAROBOTICS

🚀 Franka Research 3 now integrates with GELLO – a ROS 2-based framework for real-time teleoperation! Gripper control (Franka Hand & Robotiq) for HRI, prototyping & more. Get started: franka-community.de/t/new-release-… GitHub: github.com/wuphilipp/gell… #FrankaFR3 #ROS2 #TeleoperationFrankaFR3 #ROS2 #Teleoperation

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Xingyu Lin
Xingyu Lin@Xingyu2017·
The first edition of the workshop was a hit — so we’re bringing it back, this time in LA!
Youngwoon Lee@YoungwoonLee

#RSS2025 Workshop on Whole-Body Control & Bimanual Manipulation: Applications in Humanoids & Beyond 🤖 Join us with our amazing lineup of speakers from academia & industry! Share your latest work by May 23 wcbm-workshop.github.io @RoboticsSciSys

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Remi Cadene
Remi Cadene@RemiCadene·
Meet SO-101, next-gen robot arm for all, by @huggingface 🤗 Enables smooth takeover to boost AI capabilities, faster assembly (20mn), same affordable price ($100 per arm) 🤯 Get yours today! Links in thread below 👇
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Yahvin G
Yahvin G@yahvingali·
@Xingyu2017 @giffmana Hi Xingyu. Is there a possibility in the future for internships on this team for undergraduate/graduate students?
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Xingyu Lin
Xingyu Lin@Xingyu2017·
The robot learning team at OpenAI is hiring. We're a small, talented team building the robotics stack from zero to one, exploring fundamental questions in robot foundation models. Join us to shape the future of intelligent robots! openai.com/careers/resear…
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Xingyu Lin
Xingyu Lin@Xingyu2017·
@rraj421 Yes, but also multimodal pre-trained models that can perceive and reason.
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Rish
Rish@rish_1024·
@Xingyu2017 are you guys using llms for decision making for the robots.
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Xingyu Lin
Xingyu Lin@Xingyu2017·
@sruj_d We are hiring both senior and junior positions. This JD is for both.
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Srujan Deolasee
Srujan Deolasee@sruj_d·
@Xingyu2017 Hi Xingyu, do you anticipate to have any new grad positions in the near future? I’m assuming this one isn’t as it asks for experience managing a team of REs.
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Fan Shi
Fan Shi@fanshi_robot·
Excited to be part of this project to reduce noise in Sony Aibo robot, making them more suitable for human-centered deployment! We also believe industry and academia will collaborate more closely to solve real-world challenges. Again, kudos to Watanabe-san!
Robotic Systems Lab@leggedrobotics

Check out our #ICRA2025 paper where we train a home robot to walk quietly! Project site: sony.github.io/QuietWalk/ Video: youtube.com/watch?v=6RjkBH… Authors: Ryo Watanabe, Takahiro Miki, Fan Shi, Yuki Kadokawa, Filip Bjelonic, Kento Kawaharazuka, Andrei Cramariuc and Marco Hutter

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Tao Chen
Tao Chen@taochenshh·
Introducing Vega: our first general-purpose robot developed in under 6 months at @DexmateAI ! 🤖✨ 💪 High-payload arms for heavy lifting 🖐️ Dexterous hands for challenging manipulation tasks 📏 Foldable torso & arms -- compact for transport, yet reaches up to 7'2" 🔄 Omni-directional base movement for superior mobility 🔋 10+ hour operation time, say goodbye to frequent recharging Incredibly proud of our team's innovation. What would you use Vega for? Stay tuned for the release of our real robot. 🚀
Dexmate@DexmateAI

Introducing Vega: 🤖 @DexmateAI's newest robot that makes complex manipulation tasks simple. ✨ A step closer to intelligence and automation. 🚀 🎥 Watch now: youtu.be/PecqfiJNwQI #Robotics #AI #Automation

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Xingyu Lin
Xingyu Lin@Xingyu2017·
Very cool project! It resolves with a few pain points of GELLO, making contact-rich tasks easier and do not need to use rubber bands.
Jason Liu@JasonJZLiu

Low-cost teleop systems have democratized robot data collection, but they lack any force feedback, making it challenging to teleoperate contact-rich tasks. Many robot arms provide force information — a critical yet underutilized modality in robot learning. We introduce: 1. 🦾A low-cost, force-feedback-enabled teleop system. 2. 🥊Force-Attending Curriculum Training (FACTR) uses force to improve generalization in complex, contact-rich tasks. jasonjzliu.com/factr/ 🧵(1/N)

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Keşfet

@PengchuanZ @danijarh @GoogleDeepMind @V_Vanhoucke @lukaszkaiser @ashVaswani @countzerozzz @itfische