Overview
Dr. Fang leads research at the intersection of artificial intelligence, biomedical imaging, and neuroscience, developing trustworthy computational methods for extracting quantitative biomarkers from complex, multimodal data. Her work spans retinal and neuroimaging, near-infrared optical imaging, digital twins, and personalized modeling of brain stimulation to enable earlier diagnosis and precision intervention. Within nanoscience and materials research, her expertise in image reconstruction, segmentation, foundation models, and multiscale data integration provides computational tools for analyzing nano-enabled imaging and sensing platforms and translating high-dimensional measurements into biologically and clinically meaningful insights.
Awards
-Victor J. Dzau Emerging Leaders in Health and Medicine Scholar, National Academy of Medicine, 2026
-The Grainger Foundation Frontiers of Engineering Symposium Selection, National Academy of Engineering, 2026
-Doctoral Dissertation Advisor/Mentoring Award, Herbert Wertheim College of Engineering, University of Florida, 2025
-Stanford Science Visiting Professorship, Stanford University, 2024鈥�2025
-Senior Member, National Academy of Inventors, 2024
-Pioneering Research HiPerGator Award, University of Florida Research Computing, 2024
-Inaugural AI Course Award, University of Florida, 2024
-Best Paper Award, International Conference on Health Informatics (HEALTHINF/BIOSTEC), 2024
-Rising Star in Engineering, Academy of Science, Engineering, and Medicine of Florida, 2023
-Faculty Award for Excellence in Innovation, Herbert Wertheim College of Engineering, University of Florida, 2022
-Faculty Research Excellence Award, J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, 2021
-Ralph E. Powe Junior Faculty Enhancement Award, Oak Ridge Associated Universities, 2016
-Robin Sidhu Memorial Young Scientist Award, Society for Brain Mapping and Therapeutics, 2016
-Best Paper Award, IEEE International Conference on Image Processing, Institute of Electrical and Electronics Engineers, 2010
Selected Publications
Concept2Brain: An AI Model for Predicting Neurophysiological Responses to Text and Pictures. Santos-Mayo A, Gilbert F, Mirifar A, Tebbe AL, Fang R, Ding M, Keil A. , Nature Communications, 17, 8961, (2026) View Abstract
Prediction of Alzheimer鈥檚 Disease Risk Factors from Retinal Images via Deep Learning: Development and Validation of Biologically Relevant Morphological Associations in the UK Biobank. Leem, S., Yang, Y., Woods, A. J., and Fang, R., Journal of Alzheimer鈥檚 Disease, 112, 1268-1286, (2026) View Abstract
A Comprehensive Survey of Foundation Models in Medicine. Khan W, Leem S, See KB, Wong JK, Zhang S, Fang R., IEEE Reviews in Biomedical Engineering, 19, 283-304, (2025) View Abstract
Revealing Neurocognitive and Behavioral Patterns through Unsupervised Manifold Learning of Dynamic Brain Data. Zhou, Z., Liu, J., Wu, W. E., Fang, R., Liu, S., Wei, Q., Yan, R., Guo Y., Tao Q., Wang, Y., Islam, M.T., and Xing, L., Nature Computational Science, 5, 1238-1252, (2025) View Abstract
BrainSegFounder: Towards 3D Foundation Models for Neuroimage Segmentation. Cox, J., Liu, P., Stolte, S. E., Yang, Y., Liu, K., See, K. B., Ju, H., and Fang, R. , Medical Image Analysis, 97, 103301, (2024) View Abstract
Education
Ph.D., Electrical and Computer Engineering, Cornell UniversityB.S., Information Engineering, Zhejiang University