Fan Zhang, PhD
Assistant Professor of Medicine
Dr. Zhang and her lab focus on developing and using computational AI methods, cutting-edge single-cell multi-omics, and systems immunology approaches to study inflammatory disease pathogenesis. Dr. Zhang joined the faculty at CU Anschutz in January, 2022, and started her Computational and Systems Immunology Lab fanzhanglab.org in the Department of Medicine Division of Rheumatology and the Department of Biomedical Informatics Center for Health AI. Dr. Zhang is also an Investigator involved in the NIH-funded AMP RA/SLE (Accelerating Medicines Partnership Rheumatoid Arthritis and Systemic Lupus Erythematosus) and AMP AIM (Autoimmune and Immune-Mediated Diseases) Consortiums. She did her Postdoc research with Dr. Soumya Raychaudhuri on using immunogenomics and single-cell multi-omics to study autoimmune diseases at Harvard Medical School, Brigham and Women’s Hospital, and Broad Institute of Harvard/MIT (2017 - 2021). She has been leading the computational and systems immunology work on large single-cell omics data modeling for patients with rheumatoid arthritis and osteoarthritis. Before that, Fan completed her PhD (2013 - 2017) from Worcester Polytechnic Institute, Massachusetts. She developed novel statistical machine learning models under the supervision of Dr. Patrick Flaherty to characterize clinical patient heterogeneity.
Dr. Zhang has generated multiple deep collaborations with rheumatologists, immunologists, and computational biologists. She and her lab believe in collaborations, encourage sharing, and maintain scientific integrity to pursue high-quality science for translational medicine (Zhang, Jonsson, et al, Nature, 2023; Zhang, et al, Genome Medicine, 2021; Zhang, et al, Nature Immunology, 2019). She is actively recruiting graduate students, postdoc fellows, physician-scientists, and computational biologists to join her interdisciplinary team. Below are major research directions:
- We develop advanced statistical machine learning methods enabling reproducible computational science for single-cell omics
- We decipher pathogenic cells and molecular mechanisms, focusing on macrophages, T cells, and fibroblasts, for immune-mediated diseases
- We integrate cross-disease cross-tissue cross-cohort data to uncover shared and unique phenotypes for translational medicine
