Yujie (York) Zhang earned his BS in Bioengineering: Bioinformatics, with a minor in Mathematics, from the University of California, San Diego, where he focused on algorithm development for computational glycobiology. He went on to complete an MS in Biostatistics at Harvard University, during which he contributed to projects at the Dana-Farber Cancer Institute and the Broad Institute, specializing in high-performance computing for genetic sequencing data and statistical fine-mapping of GWAS. Currently, he is a graduate student in the Biological and Medical Informatics Program at UCSF, working in the Theodoris Lab. His research focuses on developing and applying advanced deep-learning methodologies to analyze multi-modal genomic and biomedical datasets. Beyond his academic pursuits, York enjoys soccer, hiking, and playing board games.