School of Engineering
Showing 31-40 of 305 Results
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Chongkai Gao
Graduate Visiting Researcher Student, Computer Science
BioChongkai is a PhD student from the National University of Singapore, and a visiting student researcher at Stanford University in Prof. Fei-Fei Li's group. His research is about building hierarchical foundation models and structured evaluation of general-purpose robot manipulation. Homepage: https://chongkaigao.com/.
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Grace Gao
Associate Professor of Aeronautics and Astronautics and, by courtesy, of Electrical Engineering
BioGrace Gao is an associate professor in the Department of Aeronautics and Astronautics at Stanford University, with a courtesy appointment in the Electrical Engineering Department. She leads the Navigation and Autonomous Vehicles Laboratory (NAV Lab) and serves as co-director of the Stanford AI Safety Center and co-lead of the Stanford SystemX Robotics area. Her research focuses on robust and secure perception, localization, and navigation, with applications in crewed and uncrewed aerial vehicles, autonomous cars, humanoid robots, and space robotics.
Prof. Gao has won numerous awards, including the NSF CAREER Award, the Institute of Navigation Early Achievement Award, the RTCA William E. Jackson Award, and the Inspiring Early Academic Career Award from Stanford University. In addition to her research achievements, she has received significant recognition for her teaching and advising, including the AIAA Stanford Chapter Excellence in Advising Award and the Excellence in Teaching Award. -
Xiaojing Gao
Assistant Professor of Chemical Engineering
Current Research and Scholarly InterestsHow do we design biological systems as “smart medicine” that sense patients’ states, process the information, and respond accordingly? To realize this vision, we will tackle fundamental challenges across different levels of complexity, such as (1) protein components that minimize their crosstalk with human cells and immunogenicity, (2) biomolecular circuits that function robustly in different cells and are easy to deliver, (3) multicellular consortia that communicate through scalable channels, and (4) therapeutic modules that interface with physiological inputs/outputs. Our engineering targets include biomolecules, molecular circuits, viruses, and cells, and our approach combines quantitative experimental analysis with computational simulation. The molecular tools we build will be applied to diverse fields such as neurobiology and cancer therapy.
