Prof. Michael I. Miga

Fellow Member | Professor of Biomedical Engineering at Vanderbilt Univ
Miga, Michael I.
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SPIE Membership: 17.7 years total | 17.7 years voting
SPIE Awards: Fellow status | Senior status
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Area of Expertise: Image Guided Procedures, Modeling for Therapeutic Bioengineering, Numerical Methods, Inverse Problems
Websites: Company Website
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Profile Summary

Michael I. Miga, Ph.D. received his B.S. and M.S. from the University of
Rhode Island in Mechanical Engineering and Applied Mechanics,
respectively. He received his Ph.D. from Dartmouth College specializing in
biomedical engineering. He joined the faculty in the Department of
Biomedical Engineering at Vanderbilt University in 2001 and is currently the
Harvie Branscomb Professor at Vanderbilt. He is a Professor of Biomedical
Engineering, Radiology and Radiological Sciences, Neurological Surgery,
and Otolaryngology - Head and Neck Surgery. He is director of the Biomedical Modeling Laboratory,
and co-founder of the Vanderbilt Institute for Surgery and Engineering (VISE, He has been PI on several NIH grants concerned with image-guided
brain, liver, kidney, and breast surgery. He is also PI and Director of a novel NIH T32 training
program entitled, ‘Training Program for Innovative Engineering Research in Surgery and
Intervention’ that is focused on the creation of translational technologies for treatment and
discovery in surgery and intervention. In 2014, Dr. Miga was inducted into the American Institute
for Medical and Biological Engineering College of Fellows which represents the top 2% of medical
and biological engineers. He served as a charter member of the Biomedical Imaging Technology
(BMIT-B) Study Section of the Center for Scientific Review at NIH from 2010-2014, and is
currently serving on the Bioengineering, Technology, and Surgical Sciences (BTSS) Study
Section as a charter member. His research interests are in image-guided surgery and
intervention, computational modeling for therapeutic applications, soft-tissue mechanics, biotransport, and inverse problems in therapeutics and imaging.

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