Dr. Yi Zhang is an accomplished computational biologist making significant contributions to the integration of machine learning with genomic medicine at Duke University. She currently serves as Assistant Professor of Neurosurgery with secondary appointments in Biostatistics and Bioinformatics and Biomedical Engineering at Duke University School of Medicine. Dr. Zhang earned her PhD in Bioengineering from the University of Illinois at Urbana-Champaign in 2019, establishing a strong foundation in quantitative approaches to biological problems. Following her doctoral work, she completed postdoctoral training at Dana-Farber Cancer Institute and Harvard University School of Public Health, where she refined her expertise in computational genomics. Her academic journey reflects a deliberate progression toward bridging computational methodologies with clinical applications in cancer research.
Dr. Zhang has pioneered integrative computational genomic methods that identify functional gene regulatory mechanisms underlying disease-associated human genetic variants, significantly advancing our understanding of genetic contributions to disease. Her laboratory focuses on developing interpretable machine learning approaches for analyzing patient-based single-cell, spatial transcriptomics, and multi-omics data, creating tools that have been rapidly adopted by the research community. A landmark achievement was her development of MetaTiME for characterizing tumor microenvironment cell states, published in Nature Communications in 2023, which has provided new insights into cancer heterogeneity. Her innovative work bridges the gap between computational methodology and practical biomedical applications, enabling more precise understanding of complex disease mechanisms at cellular resolution. These contributions have positioned her as a rising leader in computational oncology with growing influence across multiple disciplines.
As a core member of the Brain Tumor Omics Program at Duke Preston Robert Tisch Brain Tumor Center, Dr. Zhang leverages her computational expertise to develop methods for understanding incurable tumor types and improving cancer therapy efficacy. She is actively recruiting postdocs, students, and staff to join her interdisciplinary team focused on computational biology, machine learning, single-cell multi-omics, spatial transcriptomics, and tumor immunology. Dr. Zhang's ongoing research includes statistical and deep learning modeling of single-cell and spatial transcriptomics data to unravel the complexities of tumor microenvironments and disease progression. Her laboratory cultivates an interdisciplinary, inclusive, and supportive environment that welcomes computational biologists, bioinformaticians, computer scientists, and clinicians interested in collaborative cancer research. With her visionary approach to computational oncology, Dr. Zhang continues to advance methodologies that promise transformative insights into cancer biology and personalized treatment strategies.
