Scholar
Long Bai (白龙)
Google Scholar ID: v-fw-98AAAAJ
Alibaba DAMO Academy | CUHK (PhD) | TUM/USYD (Visiting)
Citations & Impact
Citations
789
H-index
17
i10-index
27
Publications
20
Co-authors
21
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Published two papers (EndoIR and SurgRef) in AAAI 2026; won the First Place Award in ACM MM 2025 RoboSoft Workshop; won the Best Poster Award in IROS 2025 Workshop on Soft Tissue Manipulation; awarded the APAB Yamaguchi Medal; won the MICCAI 2025 Young Scientist Award (SurgTPGS); received the Ant Group Intech-Future Scholarship; published multiple papers in Medical Image Analysis; joined Biomimetic Intelligence and Robotics as a Young Editorial Board Member; published papers in CoRL 2025, ACM MM 2025, IEEE ICIA 2025, and other conferences; served as an Invited Faculty at Surgical Data Science (SDS) Summer School 2025; published papers in Computerized Medical Imaging and Graphics, Advanced Intelligent Systems, and other journals; published papers in ICRA 2025, ICLR 2025, and other conferences.
Research Experience
- Working as an Algorithm Expert at Alibaba DAMO Academy, focusing on large-scale pretraining, multimodal large language models, and diagnosis foundation models in medical AI.
Education
- Received a Ph.D. degree in Electronic Engineering from The Chinese University of Hong Kong (CUHK) in 2025, advised by Prof. Hongliang Ren and Prof. Jiewen Lai, with thesis committee members Prof. Tan Lee, Prof. Qi Dou, and Prof. S. Kevin Zhou. During his Ph.D. study, he was a visiting student at Technical University of Munich (TUM), advised by Prof. Nassir Navab; and at The University of Sydney (USYD), advised by Prof. Luping Zhou. Previously, he received the B. Sc. degree in Opto-Electronics Information Science and Engineering from Beijing Institute of Technology (BIT) in 2021, advised by Prof. Kun Gao.
Background
- Currently an Algorithm Expert at Alibaba DAMO Academy. Research interests include artificial intelligence and its applications in medical image computing, human-robot interaction, and surgical data science. Recently working on vision-language understanding and generation.
Miscellany
- Interested in recruiting research interns for medical AI projects involving large-scale pretraining, multimodal large language models, and diagnosis foundation models.
