Rate My Professor Tim Duong

Tim Q. Duong, PhD, serves as Professor and Vice Chair for Research in the Department of Radiology at Albert Einstein College of Medicine and Montefiore Health System. He is also Associate Director of the Integrative Imaging and Data Science program at the Center for Health and Data Innovation and Director of the Biomedical Imaging PhD Program. Duong earned his PhD in magnetic resonance imaging, focusing on diffusion MRI and stroke, from Washington University in St. Louis in 1998, followed by postdoctoral training as an NRSA fellow at the University of Minnesota from 1998 to 2001. Previously, he was Associate Professor and Founding Director of the Yerkes Imaging Center in the Department of Neurology at Emory University from 2004 to 2008, and held positions including Professor and MRI Division Chief at the University of Texas Health Science Center at San Antonio.

The Duong Lab develops advanced MRI acquisition and analysis methods, integrating machine learning, deep learning, artificial intelligence, natural language processing, and big data analytics to address clinically impactful problems. Research applications span neurological disorders, neurodegenerative diseases, retinal conditions such as glaucoma and diabetic retinopathy, breast cancer including chemo brain effects, and COVID-19/long COVID using large electronic medical record cohorts in ATLAS/OMOP format. Key efforts include early disease detection, accurate diagnosis, prediction of disease progression and treatment responses, and characterization of pathophysiology. Duong has mentored over two dozen predoctoral students, three dozen postdoctoral fellows, and two dozen faculty members, with many advancing to tenured positions, research roles in academia and industry, or clinical medical physics. His scholarly output includes over 250 publications, with highly cited works such as 'COVID-19 image data collection: Prospective predictions are the future' (2020, cited over 1000 times), 'High-resolution mapping of iso-orientation columns by fMRI' (2000, Nature Neuroscience), 'Microvascular BOLD contribution at 4 and 7 T in the human brain' (2003, Magnetic Resonance in Medicine), and recent contributions like 'Deep learning applications to breast cancer detection by magnetic resonance imaging' (2023, Breast Cancer Research) and 'Incidence of New-Onset Hypertension Post-COVID-19' (2023, Hypertension). He contributes editorially as Associate Editor for Diagnostics.