Jie Chen (陈杰)

I am currently the Founding Director and Principal Researcher of the Large-Model Reinforcement Learning Department and the Embodied Software Systems Department at XPENG Robotics. We focus on cutting-edge technologies of embodied AI and the mass production of full-size humanoid robots, including but not limited to:

  • real-time embodied agents for long-horizon tasks
  • scaling for humanoid whole-body control
  • humanoid loco-manipulation
  • reinforcement learning training suites
  • full-stack embodied evaluation and data infrastructure
  • embodied simulation

Previously, I was a Senior Researcher and Tech Lead at Seed, ByteDance, focusing on post-training of Large Language Models (LLMs) and agentic RL. We made some contributions to ByteDance's Doubao and Seed series of models.

We are hiring — LLM Researchers, Embodied AI Researchers, LLM Infrastructure Experts, Reinforcement Learning Researchers, Software Architects, and Systems Engineers. Feel free to reach out.

We work on foundation models and full-stack infrastructures that move humanoids into the world.

News

Aug 2026 Our robotics business closed a Series A of over US$900M (valuation over US$6.3B), fueling the mass production of Physical AI.
Aug 2026 We released DeepInsight II, tracing one trace from benchmark to robot.
Aug 2026 We released Capek 0.5, an execution-centric vision-language model for embodied intelligence.
Aug 2026 We released R2S-EGO, dual-proxy refinement for sparse-capture real-to-sim.
Jul 2026 We released Athena-Brain, an efficient 8B robot brain for general intelligence and embodied interaction.
Jul 2026 We released Athena-WBC, capability-aligned policy experts for long-tail humanoid whole-body control.
Jun 2026 We released DeepInsight, a unified evaluation infrastructure across the Physical AI stack.
May 2026 We released the Engagement Process to formalize the real-time embodied agent paradigm.
May 2026 We released Vigil, disentangling world completion from self-termination in embodied agents.
Nov 2025 Our next-generation IRON humanoid robot debuted at 2025 XPENG AI Day, targeting mass production by the end of 2026.
May 2025 Seed-Coder, an open-source family of lightweight code LLMs.
Apr 2025 Seed-Thinking-v1.5, a reasoning model.
Jan 2025 Doubao 1.5 / 1.5-pro, an MoE model with an integrated training–inference design, rivaling GPT-4o on aggregate benchmarks.
Dec 2024 verl, an open-source RL training framework for LLMs, was released.
Oct 2024 SandboxFusion, an open-source secure sandbox for running and judging LLM-generated code across 20+ languages, was released.
May 2024 Doubao foundation models officially launched at the Volcano Engine FORCE conference (Doubao-Pro / Lite, 32K/128K), driving large-model adoption with aggressive pricing — the biggest milestone of the year.

Experience

Apr 2025 XPENG Robotics
Jan 2023 Seed, ByteDance
Jun 2021 ByteDance
Sep 2019 Tencent, focusing on large-scale reinforcement learning for MOBA and FPS video games.
Jul 2018 Momenta, established the reinforcement learning team for L3/L4 autonomous driving.

Education

2017–2018 Postdoctoral Research Fellow, Harvard University
2014–2017 Ph.D., The University of Hong Kong
2015–2016 Visiting Student, National University of Singapore
2009–2013 B.E., Soochow University

Selected Publications

  1. 2026
    DeepInsight II: One Trace from Benchmark to Robot
    S Li, Y Kang, W Wang, Z Zhang, J Liu, J Yao, J Chen
    arXiv preprint arXiv:2608.16556
  2. 2026
    Capek 0.5: An Execution-Centric Vision-Language Model for Embodied Intelligence
    Y Chen, W Li, Z Hu, Z Li, R Jiang, Z Gu, L Fang, J Liu, L Yi, J Chen
    arXiv preprint arXiv:2608.06756
  3. 2026
    R2S-EGO: Dual-Proxy Refinement for Sparse-Capture Real-to-Sim
    S Fang, X Deng, Y Kang, Z Li, J Chen
    arXiv preprint arXiv:2608.06827
  4. 2026
    Athena-Brain Technical Report: An Efficient Robot Brain for General Intelligence and Embodied Interaction
    J Li, J Liu, Y Cao, W Guo, J Song, X Wang, Y Zhao, J Liu, J Chen
    arXiv preprint arXiv:2607.18985
  5. 2026
    Athena-WBC: Capability-Aligned Policy Experts for Long-Tail Humanoid Whole-Body Control
    Y Jiang, N Zhang, X Yang, Y Jiang, J Chen
    arXiv preprint arXiv:2607.04837
  6. 2026
    DeepInsight: A Unified Evaluation Infrastructure Across the Physical AI Stack
    S Li, C Sun, J Zhang, Y Kang, W Wang, Y Qiu, R Jiang, H Cui, J Chen
    arXiv preprint arXiv:2606.17574
  7. 2026
    Engagement Process: Rethinking the Temporal Interface of Action and Observation
    J Li, Y Cao, J Liu, W Guo, X Wang, J Song, J Zhang, J Chen
    arXiv preprint arXiv:2605.11484
  8. 2026
    Vigil: Done, But Not Sure — Disentangling World Completion from Self-Termination in Embodied Agents
    Y Chen, R Jiang, L Fang, M Wang, Z Gu, L Yi, J Chen
    arXiv preprint arXiv:2605.08747
  9. 2025
    Teaching Language Models to Critique via Reinforcement Learning
    Z Xie, J Chen, L Chen, W Mao, J Xu, L Kong
    International Conference on Machine Learning (ICML)
  10. 2024
    FullStack Bench: Evaluating LLMs as Full Stack Coders
    Y Cheng, J Chen, J Chen, L Chen, et al.
    arXiv preprint
  11. 2024
    Unlock the Correlation between Supervised Fine-Tuning and Reinforcement Learning in Training Code Large Language Models
    J Chen, X Han, Y Ma, X Zhou, L Xiang
    arXiv preprint
  12. 2024
    Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks
    H Wang, B Liu, Y Zhang, J Chen
    arXiv preprint
  13. 2024
    Exploring Mathematical Extrapolation of Large Language Models with Synthetic Data
    H Li, Y Ma, Y Zhang, C Ye, J Chen
    Findings of the Association for Computational Linguistics: ACL
  14. 2023
    Mastering Strategy Card Game (Hearthstone) with Improved Techniques
    C Xiao, Y Zhang, X Huang, Q Huang, J Chen
    IEEE Conference on Games (CoG)
  15. 2023
    Mastering Strategy Card Game (Legends of Code and Magic) via End-to-End Policy and Optimistic Smooth Fictitious Play
    W Xi, Y Zhang, C Xiao, X Huang, S Deng, H Liang, J Chen, P Sun
    arXiv preprint arXiv:2303.04096
  16. 2022
    Policy Gradient from Demonstration and Curiosity
    J Chen, W Xu
    IEEE Transactions on Cybernetics
  17. 2017
    Data-driven Methods towards Learning the Highly Nonlinear Inverse Kinematics of Tendon-driven Surgical Manipulators
    W Xu, J Chen, HYK Lau, H Ren
    The International Journal of Medical Robotics and Computer Assisted Surgery
  18. 2016
    Motion Planning based on Learning from Demonstration for Multiple-Segment Flexible Soft Robots Actuated by Electroactive Polymers
    H Wang, J Chen, HYK Lau, H Ren
    IEEE Robotics and Automation Letters (RA-L)
  19. 2016
    Automate Surgical Tasks for a Flexible Serpentine Manipulator via Learning Actuation Space Trajectory from Demonstration
    W Xu, J Chen, HYK Lau, H Ren
    IEEE International Conference on Robotics and Automation (ICRA)