I am a PhD student at Imperial College London under the supervision of Prof. Panagiotis Angeloudis. I received my B.Eng. from Tongji University.

Previously, I was a research assistant at the MARMot Lab, National University of Singapore, advised by Prof. Guillaume Sartoretti. In Summer 2025, I was a research intern at the Search-Based Planning Lab (SBPL), Carnegie Mellon University, where I received guidance from Prof. Maxim Likhachev and Prof. Jiaoyang Li.

My current research explores cross-embodiment robot learning: how can robots with different dynamics and control capabilities learn from each other’s experience? I am particularly interested in learning transferable representations and unified policies from heterogeneous robot data, enabling knowledge transfer across platforms while mitigating negative transfer.

Research interests: Cross-embodiment robot learning, representation learning, and adaptive planning and control.


News

  • Oct 2025 – Attending CoRL 2025 in Seoul; looking forward to meeting collaborators and friends in person.
  • Sep 2025 – Presented recent work at the Stanford MSL Lab group meeting.
  • Jun 2025 – Research intern at CMU SBPL (Summer 2025).
  • Oct 2024 – Joined NUS MARMot Lab as an undergraduate research assistant.

Selected Publications

  • CogniPlan: Uncertainty-Guided Path Planning with Conditional Generative Layout Prediction (CoRL 2025)
  • Conflict-Based Search as a Protocol: A Multi-Agent Motion Planning Protocol for Heterogeneous Agents, Solvers, and Independent Tasks (ICRA 2026)

Education

  • B.Eng., Tongji University, 2022 – 2026
  • Exchange Student, National University of Singapore, 2024 – 2025

Experience

  • Undergraduate Research Assistant, MARMot Lab, NUS (2024 – 2025)
  • Research Intern, Search-Based Planning Lab, CMU (Summer 2025)
  • Teaching Assistant, Fudan University (2023 – 2024)

Honors & Awards

  • Tongji University Academic Scholarship
  • Second Prize, Chinese Mathematics Competition
  • Second Prize, International University Student Engineering Mechanics Competition

Contact