David Bani-Harouni

Technical University of Munich

Papers

1

Total Citations

13

H-Index

1

About

David Bani-Harouni is a leading researcher at the intersection of computer vision, medical AI, and surgical data science. His work focuses on developing large-scale, multimodal datasets and machine learning models to enable semantic understanding of high-intensity clinical environments, particularly the operating room. His most notable contribution is the introduction of **MM-OR**, the first large multimodal operating room dataset designed to capture complex interactions among medical staff, tools, and equipment in real surgical settings. This work, published in 2025, has already garnered 13 citations, underscoring its immediate impact on the field. By addressing the critical lack of realistic, large-scale benchmarks, Bani-Harouni’s research is paving the way for enhanced surgical assistance, improved situational awareness, and greater patient safety. His efforts are instrumental in advancing the next generation of AI-powered clinical decision support systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
13
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
MM-OR: A Large Multimodal Operating Room Dataset for Semantic Understanding of High-Intensity Surgical Environments
13 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Technical University of Munich

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago