![]() |
Dr. Guido Gerig - SCI Institute Associate DirectorProfessor of Computer Science. WEB 4893 phone (801) 585-0327 fax (801) 585-6513 This e-mail address is being protected from spambots. You need JavaScript enabled to view it |
BackgroundGuido Gerig was recruited from the University of North Carolina at Chapel Hill to the University of Utah under the USTAR program. He received his Ph.D. in 1987 from the Swiss Federal Institute of Technology, ETH Zurich, Switzerland. Guido Gerig joined the faculty at UNC Chapel Hill as Taylor Grandy professor in August 1998 and with a joint appointment in the Departments of Computer Science and Psychiatry. In 2007, he accepted a new faculty position at the School of Computing and Scientific Computing and Imaging Institute (SCI) at the University of Utah, with adjunct appointments in Biomedical Engineering and Psychiatry. Current ResponsibilitiesDr. Gerig serves as a SCI Institute USTAR faculty member. USTAR is an innovative, aggressive and far-reaching effort to bolster Utah's economy with high-paying jobs and keep the state vibrant in the Knowledge Age. The USTAR Support Coalition and the Salt Lake Chamber sought public and private investment to recruit world-class research teams in carefully targeted disciplines. These teams will develop products and services that can be commercialized in new businesses and industries. He holds the following positions:
Research InterestsGuido Gerig began research in the area of medical image analysis in 1985 at ETH Zurich, Switzerland. Since then, he has led a large number of national and international projects with close multidisciplinary collaboration between medicine, engineering, statistics, industry, and computer science. He is the director of the UTAH Center for Neuroimage Analysis (UCNIA) and supports a number of clinical neuroimaging projects with methodology for image processing, registration, atlas building, segmentation, shape analysis, and statistical analysis. Current key research topics are analysis and modeling of the early developing brain, longitudinal analysis of multi-shape complexes, and new methodologies for statistical analysis of white matter using diffusion tensor imaging. Method developments are driven by challenging clinical applications that include research in schizophrenia, autism, multiple sclerosis, infants at risk for mental illness and aging. New tools and methods are open source and are made available to public. |
|