Miguel P. Eckstein

About

Miguel P. Eckstein is a Professor of Psychological & Brain Sciences at UC Santa Barbara, with a background that includes a Bachelor Degree in Physics and Psychology from UC Berkeley and a Doctoral Degree in Cognitive Psychology from UCLA. His professional experience encompasses work at the Department of Medical Physics and Imaging at Cedars Sinai Medical Center and NASA Ames Research Center before his tenure at UC Santa Barbara. Eckstein has received numerous awards, including the Optical Society of America Young Investigator Award, the Society for Optical Engineering (SPIE) Image Perception Cum Laude Award, Cedars Sinai Young Investigator Award, the National Science Foundation CAREER Award, the National Academy of Sciences Troland Award, and a Guggenheim Fellowship. He has served in leadership roles such as chair of the Vision Technical Group of the Optical Society of America, chair of the Human Performance, Image Perception and Technology Assessment conference of the SPIE Medical Imaging Annual Meeting, and has held editorial positions including Vision Editor of the Journal of the Optical Society of America A and member of the board of editors of the Journal of Vision. Additionally, he has participated in NIH study section panels on Mechanisms of Sensory, Perceptual and Cognitive Processes and Biomedical Imaging Technology. Eckstein has published over 170 articles across a wide range of disciplines, focusing on computational human vision, visual attention, search,…

Research topics

• Computer Science
• Artificial Intelligence
• Machine Learning
• Cognitive science
• Natural Language Processing
• Sociology
• Psychology
• Epistemology
• Neuroscience
• Algorithm

Selected publications

• Counterfactual Vision-and-Language Navigation via Adversarial Path Sampler

  Lecture notes in computer science · 2020 · 76 citations

  DOI

• Diagnosing Vision-and-Language Navigation: What Really Matters

  Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · 2022 · 33 citations

  Wanrong Zhu, Yuankai Qi, Pradyumna Narayana, Kazoo Sone, Sugato Basu, Xin Wang, Qi Wu, Miguel Eckstein, William Yang Wang. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2022.

  DOI

• Influence of AI Decision Support on Radiologists’ Performance and Visual Search in Screening Mammography

  Radiology · 2025-07-01 · 11 citations

  articleOpen access

  Radiologists improved their performance at screening mammography when using artificial intelligence for decision support, focusing more on suspicious areas without requiring additional reading time.

  PublisherOA PDFDOI

• Perceptual Learning: Policy Insights From Basic Research to Real-World Applications

  Policy Insights from the Behavioral and Brain Sciences · 2023 · 8 citations

  Perceptual learning is the process by which experience alters how incoming sensory information is processed by the brain to give rise to behavior—it is critical for how humans educate children, train experts, treat diseases, and promote health and well-being throughout the lifespan. Knowledge of perceptual learning requires basic and applied research in humans and nonhuman animal models, which informs strategic targets for advancing applications. Commercial products to induce perceptual learning…

  PublisherOA PDFDOI

• Emergent neuronal mechanisms mediating covert attention in convolutional neural networks

  Proceedings of the National Academy of Sciences · 2025-11-13 · 3 citations

  articleOpen accessSenior author

  Covert visual attention allows the brain to select different regions of the visual world without eye movements. Predictive cues of a target location orient covert attention and improve perceptual performance. In most computational models, researchers explicitly incorporate an attentional mechanism that alters processing at the attended location (gain, noise reduction, divisive normalization, biased competition, Bayesian priors). Here, we assess the emergent neuronal mechanisms of Convolutional N…

  PublisherOA PDFDOI

Recent grants

• NIH Grant R01HL053455

  NIH · $2.3M · 2011

• Assessment of medical image quality with foveated search models

  NIH · $1.7M · 2015–2020

• CAREER: Quantitative Evaluation Of Attention Models Of Visual Search

  NSF · $392k · 2002–2008

Frequent coauthors

• Craig K. Abbey

  University of California, Santa Barbara

  139 shared

• Barry Giesbrecht

  University of California, Santa Barbara

  41 shared

• James S. Whiting

  Maine Medical Center

  40 shared

• Steven S. Shimozaki

  University of Leicester

  40 shared

• François Bochud

  Institute of Radiation Physics

  33 shared

• William Yang Wang

  26 shared

• Brent R. Beutter

  Ames Research Center

  25 shared

• Miguel A. Lago

  24 shared

Labs

• Vision and Image Understanding LabPI

  Not provided

Education

• B.A., Physics and Psychology

  UC Berkeley

• Ph.D., Cognitive Psychology

  UCLA

Awards & honors

• Optical Society of America Young Investigator Award
• Society for Optical Engineering (SPIE) Image Perception Cum…
• Cedars Sinai Young Investigator Award
• National Science Foundation CAREER Award
• National Academy of Sciences Troland Award

Similar researchers at University of California, Santa Barbara

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