Stanford University
Showing 36,601-36,650 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.
