Stanford University
Showing 36,601-36,700 of 37,050 Results
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Xingyuan Zhang
Ph.D. Student in Chemistry, admitted Autumn 2023
Ph.D. Minor, Computer ScienceBioPhD candidate in Chemistry and Computer Science, Wu Tsai Neurosciences and Sarafan ChEM-H Institute at Stanford University. Working on scientific machine learning, biomolecular modeling, and protein design for drug discovery and disease modeling.
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Xue Zhang
Clinical Assistant Professor, Psychiatry and Behavioral Sciences
BioDr. Xue Zhang is a Clinical Assistant Professor in the Department of Psychiatry and Behavioral Sciences at Stanford University. She received her PhD in Biomedical Engineering from Tsinghua University in 2019 and completed research training in neuroimaging and computational methods at Stanford.
Dr. Zhang’s research focuses on how individual differences in brain circuits contribute to psychiatric symptoms and treatment response. Working at the intersection of neuroimaging, computational neuroscience, and precision psychiatry, she uses functional MRI and data-driven approaches to study brain mechanisms underlying depression, PTSD, and related conditions.
A major focus of her work is understanding how rapid-acting therapeutics, including ketamine, MDMA, and psilocybin, acutely and durably modulate brain activity and connectivity. Her long-term goal is to develop personalized neuroimaging markers that can help match patients to the treatments most likely to benefit them. -
Yanxian Zhang
Postdoctoral Scholar, Endocrinology and Metabolism
BioThrough my academic training and research experience, I have cultivated a strong foundation in engineering and molecular biology. My work involves integrating diverse concepts from disciplines such as chemical engineering, protein engineering, supramolecular chemistry, and biophysics to address complex biomedical challenges. As a graduate student with Dr. Jie Zheng, my research focused on both natural and synthetic macromolecules. My research involved utilizing polymer chemistry to design biocompatible multifunctional hydrogels, as well as investigating the thermodynamics of amyloid proteins associated with neurodegenerative diseases. Leveraging my expertise in thermodynamics and supramolecular chemistry, I contributed to the study of understanding protein misfolding and aggregation. I identified sequence-independent inhibitors to prevent protein misfolding and developed a rational strategy for inhibitor design, enabling cross-interaction activity and the fluorescent detection of amyloids. Driven by a strong interest in translational research, I pursued postdoctoral training here at Stanford School of Medicine. In Dr. Danny Hung-Chieh Chou's lab at Stanford University, I received comprehensive training in peptide engineering and molecular biology. I am dedicated to addressing formulation challenges for insulin with stable ultra-concentrated and ultra-fast properties, aimed at miniaturizing insulin pumps and advancing the next-generation of insulin automatic delivery systems. This work is supported by the JDRF postdoctoral fellowship. Furthermore, I am working on therapeutics development and have successfully developed an insulin derivative that acts as a full insulin receptor antagonist. This development holds promise as a candidate for treating the rare disease of hyperinsulinism. Throughout my postdoctoral training, I have gained proficiency in grant writing, public speaking, and mentoring students. These experiences have significantly strengthened my skills as an independent investigator. Looking forward, my research goal is to develop innovative strategies that support the functionality and delivery of biological therapies.
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Yizi Zhang
Postdoctoral Scholar, Neurosurgery
BioYizi Zhang is a postdoctoral scholar at the Neural Prosthetics Translational Lab and the Linderman Lab. Yizi’s research centers on scalable, data-driven approaches to neural encoding and decoding, with a recent emphasis on foundation models for brain-computer interfaces. Yizi is broadly interested in developing AI-assisted neuroprosthetic technologies to help individuals with paralysis communicate and interact more effectively with the world.
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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 multiple grants including the NIH R01, R21, Eagles Autism Foundation Translational Grant, Alzheimer's Association Research Grant (AARG), and the Knight Initiative for Brain Resilience and the Rosenkranz Foundation Grants. 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. -
Yuan Zhang
Basic Life Research Scientist, Psych/Major Laboratories and Clinical & Translational Neurosciences Incubator
Current Role at StanfordBasic Life Research Scientist
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Zeyuan Zhang
Postdoctoral Scholar, Hematology-Oncology
BioZeyuan Zhang, Ph.D., is a Postdoctoral Scholar at Stanford University in the laboratory of Glaivy Batusli, where he is conducting research on the evolution of antibody development against the coagulation protein factor IX in hemophilia B disease models. He earned his Ph.D. in Biomedical Science from the University of Iowa, focusing on cell and developmental biology.
Dr. Zhang’s research centers on the molecular mechanisms underlying metabolic disease, with particular emphasis on organelle dysfunction in obesity. His work has provided insights into GSNOR enzymatic activity, lysosomal dysfunction, and inflammatory stress in metabolic regulation. He has also investigated transcriptional mechanisms contributing to obesity-associated hepatic dysfunction and adipose tissue homeostasis. Prior to joining Stanford, he worked as a Scientist I at Altos Labs, where he studied hepatocyte-specific rejuvenation reprogramming in fatty liver disease.
His technical expertise includes multi-omics approaches, RNA sequencing, chromatin immunoprecipitation, high-resolution respirometry, advanced imaging techniques, and in vivo mouse models. He also has extensive experience in primary cell isolation and histological analysis.
Dr. Zhang is interested in translational research that connects molecular mechanisms to therapeutic strategies, with the goal of developing innovative treatments for metabolic diseases. -
Zhe Zhang
Postdoctoral Scholar, Electrical Engineering
BioEPFL Ph.D. in Photonics 2024
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Zhenglin Zhang
Postdoctoral Scholar, Earth System Science
Current Research and Scholarly InterestsClimate change mitigation and sustainable nutrient management in agroecosystems
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Zisheng Zhang
Postdoctoral Scholar, Photon Science, SLAC
BioZisheng Zhang is an incoming Assistant Professor of Chemical Engineering, starting in Fall 2026. He is currently a Stanford Energy Fellow at SUNCAT Center for Interface Science and Catalysis, co-hosted by Dr. Frank Abild-Pedersen (SLAC) and Prof. Thomas Jaramillo (Chemical Engineering). He is interested in physics-steered, complexity-driven, and AI-accelerated simulations for understanding, design, and discovery of novel functional catalysts, materials, molecules, and interfaces.
ZZ grew up in Wuhan and received undergraduate training in both experimental and computational chemistry at South University of Science and Technology of China (with Prof. Jun Li) and University of California, Los Angeles (with Prof. Anastassia N. Alexandrova). He then stayed at UCLA and obtained his M.Sc. and Ph.D. in Theoretical and Computational Chemistry. During PhD study, he did research internship at Argonne National Lab in 2022 with Dr. Maria Chan. -
Kanhao (Alex) Zhao
Postdoctoral Scholar, Psychiatry
BioDr. Zhao is a postdoctoral researcher at Stanford University specializing in computational neuroscience, neuroimaging, and integrative multi-omics approaches to brain health. His research integrates supervised and unsupervised machine learning, functional neuroimaging, microbiome sequencing, metabolomics, and large-scale clinical datasets (e.g., Alzheimer's Disease Neuroimaging Initiative and National Health and Nutrition Examination Survey) to investigate how modifiable risk factors such as obesity, diet, and gut dysbiosis contribute to accelerated brain aging, cognitive vulnerability, and psychiatric symptoms.
His work focuses on developing multimodal frameworks that combine functional brain connectivity, cognitive and emotional phenotyping, microbiome profiles, and metabolomic signatures to uncover biological mechanisms underlying early cognitive decline and neuropsychiatric disorders. Through these approaches, Dr. Zhao aims to identify personalized intervention strategies—including dietary modification, microbiome-targeted therapies, and metabolite-guided treatments—to mitigate obesity-related brain aging and reduce the risk of cognitive impairment, Alzheimer's disease, anxiety, and depression.
In addition to translational neuroscience research, Dr. Zhao develops machine learning and computational methods for biomarker discovery, disease prediction, and precision psychiatry. His recent work also explores autonomous AI research agents and self-improving computational systems for large-scale neuroimaging and multi-omics foundational analysis. His publications were in online Nature Mental Health, Molecular Psychiatry, JAMA Network Open. He serves as a peer reviewer for leading journals, including Nature Mental Health, Medical Image Analysis, IEEE Transactions on Medical Imaging, npj Digital Health, and Neuropsychopharmacology. -
Chunmei Zhao
Chief Education Solutions Officer, Stanford Engineering Center for Global and Online Education
Current Role at StanfordChief Education Solutions Officer, Stanford Center for Global & Online Education, School of Engineering.
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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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Kewei Zhao
Postdoctoral Scholar, Photon Science, SLAC
Current Research and Scholarly InterestsInvestigation of catalytic mechanism of metalloenzyme with spectroscopy methods.
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Man Zhao
Postdoctoral Scholar, Radiation Biology
BioMy research primarily focuses on the molecular mechanisms, signaling pathways, and therapeutic targets underlying cancer metabolism, particularly the m6A demethylase FTO. I am also actively exploring the interplay between tumor metabolism and tumor immunity, with the goal of identifying novel metabolic vulnerabilities for cancer treatment.
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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.
