Vice Provost and Dean of Research
Showing 2,421-2,440 of 2,450 Results
-
Daniel Zhang
Chief of Staff, Institute for Human-Centered Artificial Intelligence (HAI)
BioDaniel Zhang is the chief of staff at the Stanford Institute for Human-Centered Artificial Intelligence (HAI). Previously, he led the Institute's policy research, outreach, and education initiatives. With the goal of developing evidence-based AI policy recommendations, his research interests lie at the intersection of technology policy, governance, and societal impact, including translational and original research on AI regulation and standards, the geopolitical implication of emerging technology, and the governance of large-scale ML models.
Daniel is also a member of the High-Level Expert Group on AI Ethics at UNESCO, advising the agency on the implementation of its Recommendation on the Ethics of AI. Previously, he was the manager of the AI Index where he lead-authored the 2021 and 2022 annual reports that measure and evaluate the rapid rate of AI advancement.
Before Stanford, he worked on global AI talent flows and security risks at the Center for Security and Emerging Technology and public education policy at the Riley Institute Center for Education and Leadership. Daniel holds a Master's in Security Studies from Georgetown University's Walsh School of Foreign Service, where he concentrated on technology policy, and a Bachelor's from Furman University. -
Harrison G. Zhang
MD Student, expected graduation Spring 2028
Ph.D. Student in Biomedical Data Science, admitted Autumn 2025
MSTP Student
Grad Student, Institute for Human-Centered Artificial Intelligence (HAI)BioHarrison is an MD-PhD student at Stanford University advancing precision medicine and global health using machine learning and genomics. He studied statistics and biology at Columbia University, where he was elected to Phi Beta Kappa and awarded Magna Cum Laude with Highest Honors in Field for his academic achievements.
-
Yu Zhang
Assistant Professor (Research) of Psychiatry and Behavioral Sciences (Public Mental Health and Population Sciences)
BioDr. Yu Zhang's research operates at the intersection of AI, translational neuroscience, and precision medicine. His work focuses on unraveling the complex neurobiological mechanisms underlying cognitive deficits, behavioral dysfunctions, and therapeutic responses in mental health disorders. By integrating advanced machine learning techniques with multimodal brain imaging modalities (e.g., fMRI, DTI, EEG), Dr. Zhang aims to identify neural signatures that reveal the heterogeneity of mental disorders across individuals. A central goal of his research is the development and validation of robust neurobiomarkers to improve diagnostic accuracy, refine prognostic assessments, and guide personalized treatment strategies. His work systematically characterizes brain function and dysfunction to optimize therapeutic interventions, including pharmacological treatments, psychotherapy, and neurostimulation. He is particularly focused on conditions such as Alzheimer’s disease and related dimentia, mood disorders, and neurodevelopmental disorders (e.g., ADHD, ASD), where individualized approaches are essential for improving patient outcomes.
Dr. Zhang has received several grants including the R01, R21, and Alzheimer's Association AARG grant. Beyond foundational research, Dr. Zhang is committed to bridging the gap between computational innovation and clinical application. By collaborating with clinicians, neuroscientists, and engineers, he strives to translate data-driven insights into actionable tools for real-world healthcare settings. His long-term vision is to enable mental health diagnostics and treatment to be guided by objective, biologically grounded biomarkers, thereby enhancing quality of life and long-term outcomes for individuals with psychiatric and neurological conditions.
The Stanford Precision NeuroIntelligence (SPNI) Lab, led by Dr. Zhang, is dedicated to advancing research in AI-driven neuroimaging and precision psychiatry. The lab develops and applies cutting-edge machine learning and deep learning methods to uncover neurobiological mechanisms associated with cognitive and behavioral dysfunctions, as well as treatment responses in mental health conditions. Its mission is to identify translational biomarkers that support precision diagnosis, prognosis, and targeted interventions for mood disorders, neurodevelopmental disorders, and neurodegenerative diseases. -
Heng Zhao
Member, Wu Tsai Neurosciences Institute
Current Research and Scholarly InterestsMy lab is focused on developing novel therapeutic methods against stroke using rodent models. We study protective effect of postconditioning, preconditioning and mild hypothermia. The rationale for studying three means of neuroprotection is that we may discover mechanisms that these treatments have in common. Conversely, if they have differing mechanisms, we will be able to offer more than one treatment for stroke and increase a patients chance for recovery.
-
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. -
Xiaolin Zheng
Professor of Mechanical Engineering, of Energy Science Engineering, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Materials Science and Engineering
BioProfessor Zheng received her Ph.D. in Mechanical & Aerospace Engineering from Princeton University (2006), B.S. in Thermal Engineering from Tsinghua University (2000). Prior to joining Stanford in 2007, Professor Zheng did her postdoctoral work in the Department of Chemistry and Chemical Biology at Harvard University. Professor Zheng is a member of MRS, ACS and combustion institute. Professor Zheng received the TR35 Award from the MIT Technology Review (2013), one of the 100 Leading Global Thinkers by the Foreign Policy Magazine (2013), 3M Nontenured Faculty Grant Award (2013), the Presidential Early Career Award (PECASE) from the white house (2009), Young Investigator Awards from the ONR (2008), DARPA (2008), Terman Fellowship from Stanford (2007), and Bernard Lewis Fellowship from the Combustion Institute (2004).
