About
Education
- M.Sc. in Data-Centric AI, HKUST(GZ)
- Joint research internship at Microsoft Research Asia
- B.Eng. in Artificial Intelligence, Southeast University
- Capstone co-supervised by the School of Architecture, Southeast University
Research Interests
AI-assisted architectural design and urban planning.
Research Methodology
Representation learning, generative models, and human-AI interaction.
Outside Work
Architecture, historical sites, music, and anime.
About Me
Iām a Research Assistant at CityMind Lab, HKUST(GZ). My recent research focuses on multimodal representation learning for unified understanding-and-generation autoregressive models in urban planning and architectural design. In artificial intelligence, I previously worked on representation learning at Microsoft Research AI for Science and the Zhongguancun Institute of AI. In architecture and urban studies, I actively collaborate with researchers from the School of Architecture at Southeast University and the Built Environment Technology Center at Tongji University on AI-assisted architectural and urban analysis and design. Beyond that, I also explored Human-AI Interaction projects on human cognition modeling and cognitive assistance at the Augmenting & People by Empowering X (APEX) Group, HKUST(GZ).
Timeline
- 2026-04 š CAGenMol was accepted to ACL 2026 Findings
- 2025-11 š¼ Joined CityMind Lab, HKUST(GZ) as a Research Assistant
- 2025-10 š Received M.Sc. in Data-Centric AI from HKUST(GZ)
- 2025-08 š¼ Began research internship at the Zhongguancun Institute of AI
- 2024-11 š Undergraduate thesis on AI for pocket park site selection accepted by the Journal of Urban Technology
- 2024-08 š¼ Began research internship at Microsoft Research AI for Science
- 2024-02 š§ Started Human-AI Interaction projects at the APEX Group, HKUST(GZ)
- 2023-09 š Started M.Sc. in Data-Centric AI at HKUST(GZ)
- 2023-06 š Received B.Eng. in Artificial Intelligence from Southeast University
- 2019-09 š Started B.Eng. in Artificial Intelligence at Southeast University
Research Pathway