School of Humanities and Sciences
Showing 271-280 of 285 Results
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Terry Winograd
Professor of Computer Science, Emeritus
BioProfessor Winograd's focus is on human-computer interaction design and the design of technologies for development. He directs the teaching programs and HCI research in the Stanford Human-Computer Interaction Group, which recently celebrated it's 20th anniversary. He is also a founding faculty member of the Hasso Plattner Institute of Design at Stanford (the "d.school") and on the faculty of the Center on Democracy, Development, and the Rule of Law (CDDRL)
Winograd was a founding member and past president of Computer Professionals for Social Responsibility. He is on a number of journal editorial boards, including Human Computer Interaction, ACM Transactions on Computer Human Interaction, and Informatica. He has advised a number of companies started by his students, including Google. In 2011 he received the ACM SIGCHI Lifetime Research Award. -
Jiajun Wu
Assistant Professor of Computer Science
BioJiajun Wu is an Assistant Professor of Computer Science at Stanford University, working on computer vision, machine learning, and computational cognitive science. Before joining Stanford, he was a Visiting Faculty Researcher at Google Research. He received his PhD in Electrical Engineering and Computer Science at Massachusetts Institute of Technology. Wu's research has been recognized through the ACM Doctoral Dissertation Award Honorable Mention, the AAAI/ACM SIGAI Doctoral Dissertation Award, the MIT George M. Sprowls PhD Thesis Award in Artificial Intelligence and Decision-Making, the 2020 Samsung AI Researcher of the Year, the IROS Best Paper Award on Cognitive Robotics, and faculty research awards and graduate fellowships from Samsung, Amazon, Facebook, Nvidia, and Adobe.
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Daniel Yamins
Assistant Professor of Psychology and of Computer Science
Current Research and Scholarly InterestsOur lab's research lies at intersection of neuroscience, artificial intelligence, psychology and large-scale data analysis. It is founded on two mutually reinforcing hypotheses:
H1. By studying how the brain solves computational challenges, we can learn to build better artificial intelligence algorithms.
H2. Through improving artificial intelligence algorithms, we'll discover better models of how the brain works.
We investigate these hypotheses using techniques from computational modeling and artificial intelligence, high-throughput neurophysiology, functional brain imaging, behavioral psychophysics, and large-scale data analysis. -
Jason Yeatman
Assistant Professor of Pediatrics (Developmental-Behavioral Pediatrics), of Education and of Psychology
BioDr. Jason Yeatman is an Assistant Professor in the Graduate School of Education and Division of Developmental and Behavioral Pediatrics at Stanford University. Dr. Yeatman completed his PhD in Psychology at Stanford where he studied the neurobiology of literacy and developed new brain imaging methods for studying the relationship between brain plasticity and learning. After finishing his PhD, he took a faculty position at the University of Washington’s Institute for Learning and Brain Sciences before returning to Stanford.
As the director of the Brain Development and Education Lab, the overarching goal of his research is to understand the mechanisms that underlie the process of learning to read, how these mechanisms differ in children with dyslexia, and to design literacy intervention programs that are effective across the wide spectrum of learning differences. His lab employs a collection of structural and functional neuroimaging measurements to study how a child’s experience with reading instruction shapes the development of brain circuits that are specialized for this unique cognitive function.
