Stanford University
Showing 35,751-35,800 of 36,203 Results
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Weiruo Zhang
Affiliate, Biomedical Data Science
BioDr. Zhang is currently a research engineer at the Department of Biomedical Data Science, and the data manager in the Center for Cancer Systems Biology at Stanford. Dr. Zhang completed her M.S. and Ph.D. in Electrical Engineering, both from Stanford University. Her Ph.D. studies focused on developing machine learning (ML) algorithms for metabolomics data analysis using graph theory. She received Young Scientist Award from the Metabolomics Society for her algorithm on metabolic network analysis delineating the effects of genetic mutants and drug treatment on the metabolome. Her postdoctoral studies at the Department of Radiology, Stanford School of Medicine, integrated radiomic, genomic, transcriptomic, histopathologic and clinical data that identified a prognostic metabolic regulation biomarker for non-small cell lung cancer. She has developed open-source computational tools that have been appreciated by the broad research community and industry, including the CELESTA algorithm which has been incorporated into commercial analytical platform of NanoString. Dr. Zhang's research has made significant impacts in the fields of spatial multi-omics and cancer systems biology, and she has authored and co-authored publications including Cell, Nature Methods, Nature Communications etc.
Dr. Zhang's current research at Stanford primarily focuses on developing and implementing ML/AI approaches to integrate and analyze multi-modality data, including spatial multi-omics, radiologic imaging, histopathologic images and clinical data. Her research aims at bridging the gap between underlying disease molecular/cellular biology and clinical assessment to improve diagnostics, prognostics and treatment strategies. -
Wubing Zhang
Postdoctoral Scholar, Stem Cell Biology and Regenerative Medicine
Current Research and Scholarly InterestsI'm interested in developing innovative methods and integrating multi-omics data to understand tumor-immune regulation and identify potential targets for cancer therapy.
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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, affiliated with the Wu Tsai Neurosciences Institute and the ChEM-H Institute at Stanford. Investigating the molecular mechanisms underlying chronic diseases, cancer and fibrosis, with interest on applying ML/DL approaches to drug discovery and disease modeling.
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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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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
