Stanford University
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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. -
Haoqi (Nina) Zhao
Acting Assistant Professor, Civil and Environmental Engineering
BioNina will join Stanford CEE as an Assistant Professor in Summer 2026. Her research bridges computational metabolomics and exposomics to uncover unknown lifestyle chemicals and their impacts on health. Nina earned her B.S. from Peking University, her Ph.D. from the University of Washington, and is currently a postdoctoral scientist at UC San Diego. She received the Pathway to Independence Award (K99/R00) from the National Institutes of Health in 2025.
The Zhao Lab at Stanford will operate at the interface of environmental chemistry, environmental health, and computational mass spectrometry. We aim to identify previously unrecognized chemical drivers that influence human and ecosystem health. We pursue this goal by developing innovative computational and analytical methods centered around untargeted mass spectrometry. Through these efforts, we aim to enable precision environmental health strategies, inform public health policies, and inspire sustainable chemical design.
Current research interests include (but are not limited to):
1.Leveraging mass spectrometry data repositories and advanced informatics tools to systematically map the chemical exposome.
2.Developing tools and resources for mass spectrometry data analysis to advance exposomics research.
3.Investigating host-microbiome-xenobiotic interactions and their impacts on human health.
4.Integrating toxicology with untargeted screening to accelerate the discovery and risk assessment of unknown molecules.
5.Pediatric environmental health: chemical exposures through breastfeeding and their implications for infant development.
6.Traffic-related chemical pollution: environmental fate, occurrence, and relevance to human exposures.
Education
Ph.D., University of Washington, Environmental Engineering (2021)
B.S., Peking University, Environmental Science (2016)
Publications
https://scholar.google.com/citations?user=xW9jBO0AAAAJ&hl=en
Email: hqzhao@stanford.edu -
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.
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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. -
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.
