I am a PhD student at UC Berkeley advised by Prof. Masayoshi Tomizuka and Prof. Andrea Bajcsy at Carnegie Mellon University.

My research lies in the intersection of robotics and AI with a focus on safe alignment between embodied agents and humans. I tackle the alignment and safety problems that emerge throughout the life-cycle of foundation models in robotics, ranging from: training (wherein we need to collect and quantify what kinds of embodied data will enable the desired robotics capabilities), to fine-tuning (wherein we must align these models with humans), to deployment (where these models must run in real-time, reliably detect out-of-distribution scenarios, and confidently hand over control to fallback-strategies). I ground my work through a variety of applications, from autonomous cars, to personalized robots, to generative AI and in experiments with real human participants.

During my PhD study, I also spent a significant amount of time at Waymo, scaling my research outcomes in driving foundation models, including pre-training, post-training preference alignment, and distillation for onboard deployment. I am fortunate to have the opportunity to work at NVIDIA Research, focusing on vision-language-action models for autonomous driving. Previously, I was a research intern at WeRide, Honda Research Institute, and Qualcomm AI Research.

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• [Feb 2025]

  I was named a Microsoft Future Leaders in Robotics and AI !

• [Jan 2025]

  I got Forbes 30 Under 30 (Asia, tech) nomination!

• [Jun 2024]

  I was named a Rising Star and won the Yunfan Award at the World Artificial Intelligence Conference this year (top 15 early career Chinese AI researchers)!

• [May 2024]

  I was named a Robotics: Science and Systems Pioneer this year (top 30 early career researchers around the world in the robotics field)!

• [Apr 2024]

  I won the 2024 Qualcomm Innovation Fellowship (32 winners in North America)!

• [Mar 2024]

  I won the finalist award in the Baidu AI Fellowship this year (top 20 Phd students in the AI field around the world)!

• [Mar 2024]

  Our work RT-X won the 2024 ICRA Best Paper, Best Student Paper, and Best Manipulation Paper!

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  [Feb 2025]

  Our paper with Waymo on efficient post-training preference alignment for motion generation is accepted by ICLR as a

  spotlight (notable top 5%)

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  [Jan 2025]

  I am co-organizing the Safely Leveraging VLMs in Robotics Workshop at ICRA with colleagues from CMU, Stanford, NVIDIA, Deepmind, Waymo, Anthropic, and MIT! Check out our exciting program!
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  [Jan 2025]

  I am co-organizing the RSS Pioneers Workshop at RSS this year!
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  [Jan 2025]

  Ever watch your imitation-based robot policy do something bizarre? Wish you could fix it—no retraining needed? Meet FOREWARN, a VLM-in-the-loop system that steers multi-modal generative policies toward the right outcomes, on the fly!
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  [Jan 2025]

  Not happy with your pre-trained robotics foundation model? Check out our paper Maximizing Alignment with Minimal Feedback to learn how we bring the success of preference alignment—popularized in non-embodied foundation models (e.g., LLMs)—to robotics foundation models!

For the most up-to-date list of publications, please see google scholar.