Ramin Zabih

Cornell University

Papers

3

Total Citations

92

H-Index

2

About

Ramin Zabih is a leading figure in computer vision and medical image analysis, with a career spanning foundational algorithmic work and impactful clinical applications. His early research established core techniques for real-time motion vision, enabling robots to perceive and navigate unstructured environments—a contribution that laid groundwork for modern autonomous systems. More recently, Zabih has applied rigorous computational methods to healthcare, notably investigating surgical outcomes. His highly cited studies on pulmonary lobectomy, including a 2016 paper (58 citations) that challenges the use of length of stay as a quality metric by revealing patient-driven variability, and a 2015 analysis of readmission factors (32 citations), have reshaped how clinicians evaluate postoperative care. By merging computer vision with evidence-based medicine, Zabih demonstrates how algorithmic thinking can solve real-world problems, from robot control to improving patient recovery. His work continues to influence both AI researchers and medical practitioners, bridging the gap between technical innovation and tangible clinical impact.

Research Focus

Key Achievements

2
H-Index
3
Papers
92
Total Citations
31
Avg Citations/Paper
🏆 Most Cited Paper
Variability in length of stay after uncomplicated pulmonary lobectomy: is length of stay a quality metric or a patient metric?
58 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: Cornell University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago