Gordon Wetzstein

Stanford University, Stanford Health Care

Papers

12

Total Citations

1,247

H-Index

10

About

Gordon Wetzstein is a pioneering computational imaging researcher whose work has fundamentally advanced how machines perceive the world beyond direct line of sight. Best known for developing breakthrough non-line-of-sight (NLOS) imaging algorithms, Wetzstein and his collaborators introduced the light-cone transform for confocal NLOS imaging (492 citations) and the fast f-k migration framework (257 citations), enabling cameras to effectively "see around corners" — a capability with profound implications for autonomous vehicles, robotics, and remote sensing. His 2020 work on confocal diffuse tomography (124 citations) extended these principles to imaging through scattering media like fog and rain, addressing critical challenges for real-world perception systems. Demonstrating remarkable breadth, Wetzstein translated NLOS concepts into the acoustic domain (102 citations) and explored end-to-end "dirty pixels" approaches that jointly optimize image acquisition and deep learning pipelines for raw sensor data. His investigations span time-of-flight depth sensing, light field photography, and most recently vision-language-action models for robotics. With thousands of citations accumulated across a decade of influential work, Wetzstein has established himself as one of the defining voices in computational photography and machine perception research.

Research Focus

Key Achievements

10
H-Index
12
Papers
1,247
Total Citations
104
Avg Citations/Paper
🏆 Most Cited Paper
Confocal non-line-of-sight imaging based on the light-cone transform
492 citations · 2018
📈 Most Prolific Year: 2018 (2 Papers)
🤝 Key Collaborators: 29
🏛 Institutions: Stanford University, Stanford Health Care

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago