Wilson S. Geisler | |
|---|---|
| Born | Wilson S. Geisler III |
| Nationality | American |
| Alma mater | Stanford University (B.A., 1971) Indiana University Bloomington (Ph.D., 1975) |
| Known for | Visual perception, Ideal observer analysis, Natural scene statistics |
| Awards |
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| Scientific career | |
| Fields | Vision science, Neuroscience, Psychology |
| Institutions | University of Texas at Austin |
| Thesis | Visual Adaptation and Inhibition (1975) |
| Doctoral advisor | S. L. Guth, Richard Shiffrin |
Wilson S. Geisler is an American vision scientist and neuroscientist, best known for his contributions to the study of visual perception, ideal observer analysis, and the statistical properties of natural scenes. He is Professor Emeritus of Psychology at the University of Texas at Austin and a Member of the National Academy of Sciences.
Geisler received his Bachelor of Arts degree in Psychology from Stanford University in 1971. He earned his Ph.D. in Psychology from Indiana University Bloomington in 1975 under the supervision of S. L. Guth and Richard Shiffrin. [1]
After completing his doctorate, Geisler joined the faculty at the University of Texas at Austin in 1975 as an assistant professor of psychology. He was promoted to associate professor in 1981 and to full professor in 1987. Over his career at Texas, he held joint appointments in the Biomedical engineering program from 1991 to 2024 and in the Institute for Neuroscience from 1994 to 2024. [2] Geisler served as director of the Center for Vision and Image Sciences from 1994 to 2001 and later as director of the Center for Perceptual Systems from 2001 to 2019 [3] and again from 2022 to 2023. [4] He held the David Wechsler Regents Chair in Psychology from 2001 to 2024 and currently holds the title of David Wechsler Regents Professor Emeritus. [5]
Geisler’s research focuses on the computational and neural mechanisms of visual perception, with an emphasis on how the human visual system performs in natural environments. [6] His work combines psychophysics, neuroscience, and computer modeling to study visual processes such as detection, discrimination, adaptation, and perceptual organization. [7]
His early research examined the relationship between retinal physiology during light and dark adaptation and human behavioral performance in detection and discrimination tasks. [8] He later investigated the role of optical and retinal factors in limiting human spatial and color vision, pioneering the application of ideal observer theory beyond simple photon detection and intensity discrimination. [9]
More recent work in Geisler’s laboratory has focused on spatial and contrast coding in the primate visual cortex, natural tasks and scene statistics, and the mathematical principles underlying perceptual performance. This includes theoretical models of eye movements during visual search and the analysis of human performance and eye movement patterns based on these models. The lab has also studied statistical properties of contours in natural scenes, [10] developed theories for optimal contour detection and interpolation, and applied these theories to human visual performance. [11]