Jiageng Mao

Introducing the USC Physical Superintelligence (PSI) Lab (psi-lab.ai). We are rebranding to better reflect our current focus. From here on out, we are tackling one thing: solving robotics and physical intelligence with every model, every bug, and every line of code. And yes, we are hiring at all levels, especially PhDs in this cycle and potential PostDocs who are excited about robotics. We hope you can join us in this journey! 1/9

How can we turn a generated video into a robotic demonstration? Check out @PointsCoder 's recent work PhysWorld. We also open-sourced the whole pipeline that hopefully can make real-to-sim simpler.

🚀 Join Us: Research Internships in Embodied Intelligence The USC Geometry, Vision, and Learning Lab (usc-gvl.github.io/) is seeking highly motivated interns to push the frontiers of AI, robotics, and 3D computer vision. You’ll work on large-scale VLA models, hardware–software co-design for robotic data collection, humanoids, and cutting-edge 3D computer vision research. 🔍 Research Areas Robot Learning — Large-scale algorithm training for embodied agents Hardware–Software Co-Design — Building next-gen robotic sensing and actuation platforms 3D Reconstruction & Perception — Neural scene representations, SLAM, and generative 3D modeling Deep Learning at Scale — Vision-language-action model development and optimization 🛠 Desired Expertise We welcome candidates with experience in one or more of the following: Robot learning algorithm development & training pipelines Hardware design for robotic platforms and sensor integration 3D reconstruction, NeRFs, and geometric deep learning Large-scale deep learning (PyTorch, JAX, distributed training) Computer vision & multimodal learning (images, videos, language, actions) 🌟 What You’ll Do Design and train large VLAs for robotic decision-making Develop novel hardware–software systems for efficient, high-quality robotic data collection Implement and benchmark state-of-the-art 3D perception and reconstruction algorithms Collaborate with a multidisciplinary team spanning AI, robotics, and computer vision 📍Commitment Duration: >= 3 month Weekly commitment: >= 20 hours, ideally 40 hours Start Date: 09/2025 📩 How to Apply USC Students: Apply here forms.gle/YCqXRF3wnksNCwYc8 Non-USC Applicants: Apply here forms.gle/wLmPS3bZNGPtSXA39

[Hiring!] I am hiring multiple PhDs @CSatUSC @USCViterbi for this cycle. If you're interested in scene representations, neural simulation, generative AI, and robotics, feel free to mention my name in your application (no need to email). For USC masters/undergrads who're interested in our research, feel free to fill in this form forms.gle/RerZfDqCqmCj8As27.

Agent-Driver is accepted to @COLM_conf with top 1% reviews (7, 7, 8, 9) among all submissions. We sincerely thank reviewers for providing super constructive comments and helping us improve this paper. We incorporated all feedback from the rebuttal and released a final version: arxiv.org/abs/2311.10813. Hopefully this 40-page report provides a comprehensive study of LLM agents applied to autonomous driving and facilitates future research ideas. Huge thanks to student leads @PointsCoder @JunjieYe9 and James Qian who spent days and nights improving every single bit of this paper and to @drmapavone for countless support of this project. Most importantly, thank you @COLM_conf organizers for putting together this timely conference and all the efforts of making the review process so smooth!

Amazing Friday! Our USC-Stanford (@USCViterbi @StanfordEng) joint team, led by students @PointsCoder @JunjieYe9 and co-advised by @drmapavone won the Qualcomm fellowship! The most proud moment in the year. Thank you @Qualcomm for supporting our research.