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BioLu Zhang, Founder and Managing Partner of Fusion Fund, is a renowned Silicon Valley-based investor, a serial entrepreneur, and a Stanford Engineering alumna. With a strong technical background, Lu has extensive experience bringing a broad range of technologies to commercialization and deep domain expertise in AI in healthcare, Enterprise AI/Networks, Edge Computing, and Data Privacy.
Prior to starting Fusion Fund, Lu was a serial entrepreneur and materials science researcher, which eventually led her to create Fusion Fund in 2015. Since then, Lu has built a distinguished eco system and established her reputation in the VC industry. She was honored as Young Global Leader by World Economic Forum (Davos), Silicon Valley Women of Influence, Best 25 Female early-stage investor by Business Insider, Featured Honoree of VC of Forbes 30 under 30 and Town & Country 50 Modern Swans - Entrepreneurship Influencer.
Lu frequently speaks at conferences such as World Economic Forum (Davos), Future Investment Initiative (FII), Web Summit, SuperReturn, etc., and is an Instructor at Stanford University. Lu also serves as a board member of many portfolio companies, the Board Director of CommonSpirit Health Foundation, the Board and Chairwomen of the Youth Council of Future Science Award, and Jury Board of the Cartier Women Initiative and Young Leader Award. She holds an M.S. in Materials Science and Engineering from Stanford University.

Contact Info
Mail Code: 2078
lzhang6@stanford.edu

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.