Efficient Pretrain
How can we build robotic foundation models efficiently when robotics data are limited?
Explore this workEMBODIED AI & REINFORCEMENT LEARNING
李健雄
Co-founder & CEO / BASAL Intelligence
Hi! I study embodied AI and reinforcement learning. My dream is to develop robots that are universally deployable across diverse real-world environments.
I completed my PhD at AIR, Tsinghua University in July 2026, advised by Prof. Xianyuan Zhan and Prof. Ya-Qin Zhang.
Previously, I was a Top Seed at ByteDance Seed Robotics (December 2025–July 2026), working closely with Xiao Ma. I received my bachelor's degree in 2021 from the School of Mechanical Engineering at Xi'an Jiaotong University, where I worked on mechanical design and robotics projects.

01 / RESEARCH
Three questions that guide my work.
How can we build robotic foundation models efficiently when robotics data are limited?
Explore this workHow can we rapidly enhance robot performance with a limited budget?
Explore this workHow can reinforcement learning achieve super-human performance across robots, VLMs, and LLMs?
Explore this work02 / UPDATES
I co-founded BASAL Intelligence and serve as CEO.
I completed my PhD at Tsinghua University, advised by Prof. Xianyuan Zhan and Prof. Ya-Qin Zhang. My thesis focused on Data Flywheel for Intelligent Decision-Making.
New work: World Value Models and TTT-VLA — value modeling and test-time adaptation for robotic manipulation.
Demystifying Action Space Design is accepted to ICML 2026 and received the Best Paper Award at the Efficient Spatial Reasoning Workshop @ ICLR 2026.
Three papers have been accepted to ICLR 2026, including a strong VLA model X-VLA, a stable diffusion RL post-training approch DIPOLE and a sample-efficient offline RL approch TELS.
🏆Our X-VLA has won 1st place in the AGIBOT World Challenge (Manipulation track) @ IROS 2025.
🌟We release X-VLA, a cross-embodiment model that sweeps many benchmarks and achieves strong real-world performance.
One paper (FlowPlanner) on autonomous driving is accepeted to NeurIPS 2025.
One paper (LBP) on efficient latent planning is accepted to ICML 2025.
One paper (UniAct) on cross-embodiment universal actions is accepted to CVPR 2025.
🌟Diffusion-Planner is selected as oral presentation at ICLR 2025.
Two papers on fast post-train (PSEC) and autonomous driving (Diffusion-Planner) are accepted to ICLR 2025.
One paper (Robo-MUTUAL) on embodied representations is accepted to ICRA 2025.
🌟One paper (RSP) on offline RL is accepted to AAAI 2025 as oral.
🌟IVM and DecisionNCE are selected as Outstanding Paper at MFM-EAI workshop @ ICML 2024.
03 / PUBLICATIONS
Best Paper · Efficient Spatial Reasoning Workshop @ ICLR 2026
Conference title: Sample Efficient Offline RL via T-Symmetry Enforced Latent State-Stitching
1st place @ AGIBOT World Challenge (Manipulation track), IROS 2025
Oral, Top 2%
Outstanding Paper @ ICML 2024 MFM-EAI Workshop
Outstanding Paper @ ICML 2024 MFM-EAI Workshop
Spotlight, Top 5%
Oral, Top 5%
Also presented at NeurIPS 2024 OWA Workshop
Oral, Notable Top 5%
Oral, Top 2%
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Publication updates verified against Google Scholar and original papers · September 2026.
04 / EXPERIENCE & EDUCATION
Co-founder & CEO
Co-founded BASAL Intelligence in July 2026.
PhD · Institute for AI Industry Research (AIR)
Advised by Prof. Xianyuan Zhan and Prof. Ya-Qin Zhang.
Bachelor's degree · School of Mechanical Engineering
Projects in mechanical design and robotics.
05 / COMMUNITY
Reviewer for ICLR 24–25 (Notable Reviewer), ICML 24–25, NeurIPS 23–25 (Top Reviewer), AAAI 24–25, IJCAI 24, IROS, TMLR, ICLR 2025 Workshop @ World Models, and ICLR 2024 Workshop @ DMLR.
LET'S CONNECT
If you're deeply passionate about robot learning and eager to push the limits and advance the field, we'd love to have you join us.