Location
S253 Wyman Park Building
Research Areas Biomedical data science Computational biology Genomics Machine learning Single-cell and spatial omics

Jean Fan is an assistant professor in the Department of Biomedical Engineering at Johns Hopkins University.

Her research team, the JEFworks lab, is interested in understanding the molecular and spatial-contextual factors shaping cellular identity and heterogeneity. She develops machine learning and statistical approaches as open-source software for analyze high-dimensional, single cell and spatially resolved multi-omic data. Focused on understanding the spatial regulatory mechanisms that shape cellular identity and disease progression, Fan and her lab use cutting-edge imaging and sequencing technologies to characterize the organization cells within tissues. By developing novel computational tools to analyze these complex data sets, Fan and her lab are advancing our understanding of how cellular heterogeneity contributes to disease pathogenesis, progression, and prognosis. Fan is also the founder, director, and lead software developer for the non-profit organization CuSTEMized, which provides personalized STEM picture storybooks to encourage young girls to see themselves as scientists. The impact of her work has been recognized by several awards and honors, including the Presidential Early Career Award for Scientists and Engineers, Forbes 30 Under 30, the Nature Research Award for Inspiring Science, the NSF CAREER Award, and the NIH Maximizing Investigators’ Research Award.

Fan was previously an NCI F99/K00 post-doctoral fellow in the lab of Xiaowei Zhuang at Harvard University where she developed computational methods for analyzing spatially resolved transcriptomics data and applied MERFISH to characterize cellular and subcellular heterogeneity. She received her PhD in Bioinformatics and Integrative Genomics at Harvard under the mentorship of eter Kharchenko at the Department of Biomedical Informatics and in close collaboration with Catherine Wu at the Dana-Farber Cancer Institute where she developed computational methods for analyzing single-cell omics data to better understand the disease pathogenesis and progression of chronic lymphocytic leukemia.

Students interested in getting involved with the lab are encouraged to check out the JEFworks Lab website for more details.