School of Medicine
Showing 12,721-12,740 of 12,893 Results
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Huaiyu Zhang
Clinical Assistant Professor, Medicine - Cardiovascular Medicine
BioDr. Zhang obtained her MS in Neuroscience from the University of Southern California and earned her PhD in Clinical Psychology from Emory University. She completed both her predoctoral internship and postdoctoral fellowship at Emory University School of Medicine. Prior to joining Stanford in 2023, Dr. Zhang supported survivors of interpersonal violence at the University of California San Francisco Trauma Recovery Center for over seven years. Dr. Zhang embraces an integrative, contextualized, evidence-informed, and strength-based approach to teaching, supervision, and clinical care. She provides services in English and Mandarin.
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Lu Zhang
Postdoctoral Scholar, Endocrinology and Metabolism
BioLu is a postdoctoral research scholar in Dr. Anna Gloyn's Translational Genomics of Diabetes Lab. During her master's and doctoral studies, she focused on epigenomics and single-cell multi-omics analysis, with an emphasis on 3D genomics. Her research included developing Hi-Tag, a chromatin conformation capture technique designed for use with small cell samples. This method provides valuable insights into the organization of chromatin in the cell. She has built strong expertise in combining different types of biological data, including RNA-seq, ATAC-seq, chromatin interaction data, and single-cell data. She has contributed to several research projects as a co-author, including studies that used genome-wide association studies (GWAS) and GTEX data to connect multi-omics data with functional genomics. These experiences have helped her gain a deep understanding of how to integrate different types of genomic data to solve complex biological problems. Currently, Lu is focused on applying her research skills to diabetes.
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Mengrui Zhang
Senior Biostatistician, Med/Quantitative Sciences Unit
BioMengrui’s research focuses on leveraging advanced statistical and machine-learning techniques to extract meaningful insights from complex biological datasets. His research interests include bioinformatics, deep learning/machine learning, statistical testing, high-dimensional data, non-parametric modeling, time series analysis, and spatial statistics. Additionally, he is also interested in developing new methods, tools, and pipelines for various kinds of biological datasets, especially in single cell, RNA-Seq, metagenomics, and proteomics to support drug discovery and development.