Long Bai

Long Bai is an Algorithm Expert (Senior Research Scientist) at the Alibaba DAMO Academy and a PhD candidate in Electronic Engineering at The Chinese University of Hong Kong (CUHK) since 2021. He is also a Visiting Student at the Technical University of Munich (TUM) since 2024, affiliated with the Chair of Computer Aided Medical Procedures (CAMP) under Prof. Nassir Navab.

• PhD Student, CUHK (2021–Present)
• Visiting Student, CAMP, TUM (2024–Present)
• Algorithm Expert, Alibaba DAMO Academy (2025–Present)

His research focuses on multimodal AI, medical image analysis, surgical data science, and vision-language models for robotic surgery. He has pioneered work in 4D Gaussian Splatting for endoscopic scene reconstruction, diffusion models for surgical video generation, and transformer-based architectures for depth estimation.

His recent publications include 15+ works in top venues like MICCAI, IROS, and CoRL, with key themes in endoscopic surgery, human-robot interaction, and vision-language-action systems. Awards include the MICCAI 2024 Best Paper Runner Up, IPCAI 2024 Best Paper Shortlist, and multiple IEEE Travel Grants.

He has mentored over 15 students and interns, including Junyi Wang (PhD, NUS) and Boyi Ma (PhD, University of Toronto). He also serves on editorial boards and conference committees for MICCAI, ICRA, and IROS.