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Stanford Aging and Ethnogeriatrics Research Center (SAGE Center)

Stanford Aging and Ethnogeriatrics Research Center (SAGE Center)

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SAGE awardees

Jiajun Wu, Ph.D.

Assistant Professor
Computer Science

https://profiles.stanford.edu/jiajun-wu

Jiajun Wu is an Assistant Professor of Computer Science at Stanford University, affiliated with the Stanford Vision and Learning Lab (SVL) and the Stanford AI Lab (SAIL). His research focuses 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 the Massachusetts Institute of Technology. Dr. Wu’s research has been funded by the National Science Foundation, the National Institutes of Health, the Stanford Center for Human-Centered Artificial Intelligence, Ford Motor Company, the Toyota Research Institute, Meta Platforms, Inc., and others.

Wu’s research has been recognized through the AFOSR Young Investigator Research Program (YIP), 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 from JPMC, Samsung, Amazon, and Meta.

SAGE Project: Development of computer technologies for integration into assistive systems for older adults

For computers and intelligent systems that can assist and interact with older adults, one major developmental challenge is their ability to perceive people in their everyday surroundings. In computer vision, there have been disruptive advancements in 3D perception algorithms that recover rich human states, including their body shapes, kinematic pose, facial expression, and hand poses from raw visual input. The project goal is to incorporate this technology into assistive human-robot interaction scenarios, which will provide the opportunity for robots to more effectively interact and support older adults.

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    Next-Generation Artificial Intelligence for Diagnosis: From Predicting Diagnostic Labels to "Wayfinding"

    Julia Adler-Milstein, PhD1; Jonathan H. Chen, MD, PhD; Gurpreet Dhaliwal, MD

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