Siyuan Yan

Monash University

Papers

1

Total Citations

15

H-Index

1

About

Siyuan Yan is a rising researcher in the field of artificial intelligence for healthcare, with a primary focus on surgical workflow understanding and ophthalmic medical imaging. His most notable contribution is the creation of OphNet, a large-scale video benchmark designed to advance the automated analysis of ophthalmic surgical procedures. This work, published in 2024, has already garnered 15 citations, signaling its rapid impact on the computer vision and surgical AI communities. By providing a comprehensive, annotated dataset, Yan’s research enables more precise recognition of surgical phases, instrument usage, and critical events during eye surgery—a crucial step toward developing intelligent systems that can assist surgeons and improve patient outcomes. His efforts bridge the gap between clinical ophthalmology and deep learning, offering a foundational resource for future studies in surgical workflow understanding. Yan’s work is particularly notable for its potential to enhance training, safety, and efficiency in ophthalmology, positioning him as an emerging leader in the intersection of medical AI and surgical video analysis.

Research Focus

Key Achievements

1
H-Index
1
Papers
15
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
OphNet: A Large-Scale Video Benchmark for Ophthalmic Surgical Workflow Understanding
15 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Monash University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago