Stanford University
Showing 451-500 of 777 Results
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Renee Zhao
Assistant Professor of Mechanical Engineering and, by courtesy, of Bioengineering and of Materials Science and Engineering
BioRuike Renee Zhao is an Assistant Professor of Mechanical Engineering at Stanford University, where she directs the Soft Intelligent Materials Laboratory. Originally from the historic city of Xi'an, she earned her BS from Xi'an Jiaotong University in 2012. She then pursued Solid Mechanics at Brown University, obtaining her MS in 2014 and PhD in 2016. Following her doctoral studies, she completed postdoctoral training at MIT (2016–2018) before serving as an Assistant Professor at The Ohio State University (2018–2021).
Renee’s research focuses on developing stimuli-responsive soft composites for multifunctional robotic systems with integrated shape-changing, assembly, sensing, and navigation capabilities. By integrating mechanics, material science, and advanced material manufacturing, her work enables innovations in soft robotics, miniaturized biomedical devices, robotic surgery, origami systems, active metamaterials, and general deployable morphing structures.
Her contributions have been recognized with honors and awards, including the Presidential Early Career Award for Scientists and Engineers (PECASE), DARPA Young Faculty Award (YFA, 2025), ARO Early Career Program (ECP) Award (2023), AFOSR Young Investigator Research Program (YIP) Award (2023), Eshelby Mechanics Award for Young Faculty (2022), ASME Henry Hess Early Career Publication Award (2022), ASME Pi Tau Sigma Gold Medal (2022), ASME Applied Mechanics Division Journal of Applied Mechanics Award (2021), NSF CAREER Award (2020), and ASME Applied Mechanics Division Haythornthwaite Research Initiation Award (2018). She is also recognized as a National Academy of Sciences Kavli Fellow and was named one of MIT Technology Review's 35 Innovators Under 35. -
Tianyu Zhao
Postdoctoral Scholar, Radiation Biology
Current Research and Scholarly InterestsHow p53 affects the tissue homeostasis in lung cancer and injury.
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Yanan Zhao
Postdoctoral Scholar, Psychiatry
BioYanan completed her Ph.D. degree at Fudan University, where she uncovered the mechanisms of sleep transitions from the evolutionary point of view in Dr Zhili Huang’s lab, with a combination of optogenetics, in vivo electrophysiology, fiber photometry, polysomnography, immunohistochemistry and so on. In the de Lecea lab, Yanan is now curious about how sleep regulates the balance between DNA damage and repair with approaches of imaging. At the same time, she is interested in larger scale imaging during different brain states. Outside the lab, Yanan enjoys biking and exploring the sunny bay area.
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Moss Zhao
Instructor, Neurosurgery
BioDr. Moss Zhao is an Instructor at Department of Neurosurgery, Stanford University. He develops cutting-edge and clinically viable imaging technologies to improve the diagnosis and treatment of cerebrovascular diseases across the lifespan. His specific areas of expertise include physiological modeling, arterial spin labeling, Bayesian inference, PET/MRI, and artificial intelligence. His scientific contributions could significantly improve the early detection of strokes and dementia as well as enrich the knowledge of brain development in the first two decades of life.
Dr. Zhao received his DPhil at St Cross College of University of Oxford under the supervision of Prof. Michael Chappell. As an alumni mentor, he supports the career development of students of his alma mater. Since 2016, he has presented his work to more than 3000 delegates at international conferences and held leadership positions in professional societies. His research and teaching are supported by the American Heart Association, the National Institutes of Health, and the European Cooperation in Science and Technology. -
Hong Zheng
Research Engineer, Med/BMIR-ITI Institute
BioMy research focuses on understanding the multi-omic landscape (genomics, epigenomics, transcriptomics, etc.) and immune responses in human diseases (cancer, aging, and infectious diseases, etc.), and identifying robust gene signatures and targets for disease diagnostics, prognostics, and therapeutics.
