Dr. Ruogu “Rena” Fang

An AI researcher in medicine and healthcare, Dr. Ruogu Fang is the Flowers Family Dean’s Faculty Fellow in Engineering in the Department of Biomedical Engineering at Vanderbilt University. Her research encompasses two principal themes: AI-empowered precision brain health and brain/bio-inspired AI.

Her work involves addressing compelling questions, such as using machine learning techniques to quantify brain dynamics, facilitating early Alzheimer's disease diagnosis through novel imagery, predicting personalized treatment outcomes, designing precision interventions, and leveraging principles from neuroscience to develop the next generation of AI. Dr. Fang is ranked among the Top 100 (top 1%) researchers worldwide in image analysis, according to ScholarGPS.

Fang's current research is also rooted in the confluence of AI and multimodal medical image analysis. She is the PI of NIH NIA and NIMH awards (RF1AG071469 and R01MH112558), an NSF Research Initiation Initiative (CRII) Award (IIS-1564892), an NSF CISE IIS Award (IIS-1908299), and the NSF NCS-FO Award (NCS-FO-2318984), as well as a Ralph Lowe Junior Faculty Enhancement Award from Oak Ridge Associated Universities (ORAU). She has also received numerous recognitions, including selection as a Victor J. Dzau Emerging Leaders in Health and Medicine Scholar by the National Academy of Medicine, selection for the Grainger Foundation Frontiers of Engineering Symposium by the National Academy of Engineering, a Stanford Science Faculty Fellowship, selection as a Rising Star in Engineering by the Academy of Science, Engineering, and Medicine of Florida (ASEMFL), the inaugural Robin Sidhu Memorial Young Scientist Award from the Society of Brain Mapping and Therapeutics, a Best Paper Award from the IEEE International Conference on Image Processing, the University of Florida AI Course Award, a UF Herbert Wertheim College of Engineering Faculty Award for Excellence in Innovation, and UF BME Faculty Research Excellence Award and Faculty Teaching Excellence Award.

Fang's research has been featured by Forbes Magazine, The Washington Post, ABC, and RSNA. Her work has appeared in Lancet Digital Health, JAMA, PNAS, Nature Communications, Nature Computational Science, npj Digital Medicine, npj Women's Health, and top conferences such as ICCV and MICCAI. She is the President of Women in MICCAI (WiM), an Associate Editor of Medical Image Analysis, a Topic Editor of Frontiers in Human Neuroscience, a Guest Editor of Computerized Medical Imaging and Graphics, and a reviewer for The Lancet, Nature Machine Intelligence, and Science Advances. Her research has been supported by NSF, NIH, ORAU, DHS, DoD, NVIDIA, and the University of Florida. At the heart of her work is the Smart Medical Informatics Learning and Evaluation (SMILE) Lab, where she develops medical AI and deep learning models to comprehend, diagnose, and treat brain disorders while navigating extensive and intricate datasets.