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Bennett Landman, Ph.D.

Bennett Landman computer engineering and electrical engineering. In his Medical-image Analysis and Statistical Interpretation (MASI) lab (John Russell/Vanderbilt University)Landman_Bennett1

Professor, Chancellor Faculty Fellow

Department of Electrical Engineering (primary)
Department of Computer Science
Department of Biomedical Engineering
Department of Radiology and Radiological Sciences
Department of Psychiatry and Behavioral Sciences</a
Department of Biomedical Informatics
Vanderbilt University Institute of Image Science
Vanderbilt Brain Institute
Vanderbilt Kennedy Center
Vanderbilt University, School of Engineering

 Brief Bio

Bennett A. Landman, Ph.D. is currently a Professor of Electrical Engineering at Vanderbilt University, with appointments in Computer Science, Biomedical Engineering, Radiology and Radiological Sciences, Psychiatry and Behavioral Sciences, and Biomedical Informatics. He graduated with a bachelor of science (’01) and master of engineering (’02) in electrical engineering and computer science from the Massachusetts Institute of Technology, Cambridge, MA. After graduation, he worked in an image processing startup company and a private medical imaging research firm before returning for a doctorate in biomedical engineering (‘08) from Johns Hopkins University School of Medicine, Baltimore, MD. Since 2010, he has been with the Faculty of the Electrical Engineering and Computer Science Department, Vanderbilt University, Nashville, TN. His research concentrates on applying image-processing technologies to leverage large-scale imaging studies to improve understanding of individual anatomy and personalize medicine.

Dr. Landman has received grant funding from the National Institutes of Health, the National Science Foundation, the Department of Defense, Incyte Corporation, and 12 Sigma Technologies. He is highly collaborative with 340+ co-authors across disciplines, career stages, and institutions, resulting in 185+ peer-reviewed journal publications and 7,290+ citations. He in on the MICCAI Society Challenge Working Group, is co-chair of the SPIE Medical Imaging Image Processing conference (2017-2021), co-chair of the SIIM Machine Learning Tools Committee (2018-present), and on the editorial boards of the IEEE Transactions of Medical Imaging and SIIM Journal of Digital Imaging. He has organized 9 workshops and challenges at MICCAI since 2011 and has supported challenges with SPIE, ISBI, ISMRM, and Kaggle. He serves as the Principal Scientist of ImageVU, Vanderbilt’s clinical data reuse initiative in Radiology, director of the Center for Computational Imaging at the Vanderbilt University Institute of Image Science, and chair of the faculty advisory board of the Vanderbilt University Advanced Computing Center for Research and Education (ACCRE).


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Office: 372 Jacobs Hall


Phone: (615) 322-2338 FAX: (615) 343-5459



Ph.D. 2008 Biomedical Engineering 
Johns Hopkins University School of Medicine, Baltimore, MD
Thesis: Diffusion Imaging of the In Vivo Spinal Cord and Cerebellum
Advised by Jerry Prince and Susumu Mori. Image Analysis and Communications Laboratory.

M.Eng. 2002 Electrical Engineering and Computer Science
Massachusetts Institute of Technology, Cambridge, MA
Thesis: Broadband Nanosensing using Heterodyne Interferometry.
Advised by Dennis Freeman. Research Laboratory for Electronics.

B.S. 2001 Electrical Engineering and Computer Science
Massachusetts Institute of Technology, Cambridge, MA
Minors in Mechanical Engineering and Economics.