Guillermo Sapiro received his B.Sc. (summa cum laude), M.Sc., and Ph.D. from the Department of Electrical Engineering at the Technion, Israel Institute of Technology. After post-doctoral research at MIT, he became Member of Technical Staff at the research facilities of HP Labs in Palo Alto, California, where he co-developed the image compression techniques used in the original Mars Rovers expedition. He was with the Department of Electrical and Computer Engineering at the University of Minnesota, where he held the position of Distinguished McKnight University Professor and Vincentine Hermes-Luh Chair in Electrical and Computer Engineering. Currently he is with Duke University. His awards include the Office of Naval Research Young Investigator Award in 1998, the Presidential Early Career Awards for Scientist and Engineers (PECASE) in 1998 (awarded in the White House by President Clinton), the National Science Foundation Career Award in 1999, the National Security Science and Engineering Faculty Fellowship in 2010, and the Test of Time Award in 2011 for his paper on image segmentation. His algorithms appear in Adobe’s products, leading medical imaging packages such as ITK, and are also roaming on Mars. He has been teaching image processing for over 15 years and delivered numerous invited plenary talks and short courses at leading imaging and applied mathematics conferences. G. Sapiro is the founding Editor-in-Chief of the SIAM Journal on Imaging Sciences, currently ranked as the second highest impact journal in the whole discipline of applied mathematics.
These cookies are necessary for the website to function and cannot be switched off in our systems. They are usually only set in response to actions made by you which amount to a request for services, such as setting your privacy preferences, logging in or filling in forms. You can set your browser to block or alert you about these cookies, but some parts of the site will not then work.
These cookies may be set through our site by our advertising partners. They may be used by those companies to build a profile of your interests and show you relevant adverts on other sites. They are based on uniquely identifying your browser and internet device. If you do not allow these cookies, you will experience less targeted advertising.
These cookies allow us to count visits and traffic sources so we can measure and improve the performance of our site. They help us to know which pages are the most and least popular and see how visitors move around the site. If you do not allow these cookies we will not know when you have visited our site, and will not be able to monitor its performance.
These cookies enable the website to provide enhanced functionality and personalization. They may be set by us or by third party providers whose services we have added to our pages. If you do not allow these cookies then some or all of these services may not function properly.