Tanner Watts

University of Utah

Papers

1

Total Citations

2

H-Index

1

About

Tanner Watts is a rising figure at the intersection of computer vision and surgical robotics, with a primary focus on enabling autonomous action from limited sensory data. His most cited work, "From Monocular Vision to Autonomous Action: Guiding Tumor Resection via 3D Reconstruction," tackles a critical bottleneck in surgical automation: the reliance on bulky depth sensors. By demonstrating that a single, small monocular camera—ideal for space-constrained clinical settings—can generate precise 3D anatomical maps to guide tumor resection, Watts has proposed a pathway toward truly minimally invasive autonomous surgery. While his citation count is still nascent (2 citations for this landmark 2025 paper), the work signals a significant conceptual shift, moving the field away from hardware-heavy solutions toward smarter, software-driven perception. This contribution positions him as a key innovator in translating computer vision principles directly into life-saving clinical tools.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
From Monocular Vision to Autonomous Action: Guiding Tumor Resection via 3D Reconstruction
2 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: University of Utah

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago