Edmund T. Pratt, Jr. School Professor of Electrical and Computer Engineering
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, in 1989, 1991, and 1993 respectively. After post-doctoral research at MIT, Dr. Sapiro became Member of Technical Staff at the research facilities of HP Labs in Palo Alto, California. 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 the Edmund T. Pratt, Jr. School Professor with Duke University.
G. Sapiro works on theory and applications in computer vision, computer graphics, medical imaging, image analysis, and machine learning. He has authored and co-authored over 300 papers in these areas and has written a book published by Cambridge University Press, January 2001.
G. Sapiro was awarded the Gutwirth Scholarship for Special Excellence in Graduate Studies in 1991, the Ollendorff Fellowship for Excellence in Vision and Image Understanding Work in 1992, the Rothschild Fellowship for Post-Doctoral Studies in 1993, the Office of Naval Research Young Investigator Award in 1998, the Presidential Early Career Awards for Scientist and Engineers (PECASE) in 1998, the National Science Foundation Career Award in 1999, and the National Security Science and Engineering Faculty Fellowship in 2010. He received the test of time award at ICCV 2011.
G. Sapiro is a Fellow of IEEE and SIAM.
G. Sapiro was the founding Editor-in-Chief of the SIAM Journal on Imaging Sciences.
Appointments and Affiliations
- Edmund T. Pratt, Jr. School Professor of Electrical and Computer Engineering
- Professor of Electrical and Computer Engineering
- Professor of Biomedical Engineering
- Professor of Computer Science
- Faculty Network Member of the Duke Institute for Brain Sciences
- D.Sc. Israel Institute of Technology, 1993
Image and video processing, computer vision, computer graphics, computational vision, biomedical imaging, brain imaging, cryo-tomography of viruses, computational tools in cryo-tomography, computational tools in early diagnosis of psychiatric disorders, differential geometry and differential equations, scientific computation, learning and high dimensional data analysis, sparse modeling and dictionary learning, applied mathematics.
Awards, Honors, and Distinctions
- Distinguished Israel Pollack Lecturer, Technion, Haifa.. Technion, Israel. 2016
- Plenary Speaker, European Signal Processing Conference (EUSIPCO). EUSIPCO. 2014
- Fellows. Institute for Electrical and Electronics Engineers. 2014
- Member, National Academies’ Board on Mathematical Sciences and their Applications (BMSA).. National Academies. 2014
- Science Advisory Board, Institute for Computational and Experimental Research in Mathematics (ICERM), Brown University.. ICERM. 2014
- Fellow. Society for Industrial and Applied Mathematics. 2013
- COMPSCI 391: Independent Study
- COMPSCI 393: Research Independent Study
- ECE 391: Undergraduate Research in Electrical and Computer Engineering
- ECE 392: Undergraduate Research in Electrical and Computer Engineering
- ECE 590: Advanced Topics in Electrical and Computer Engineering
- ECE 899: Special Readings in Electrical Engineering
- Delbracio, M; Sapiro, G, Removing Camera Shake via Weighted Fourier Burst Accumulation, IEEE Transactions on Image Processing, vol 24 no. 11 (2015), pp. 3293-3307 [10.1109/TIP.2015.2442914] [abs].
- Lucas, JE; Sapiro, G, Cancer: What's luck got to do with it?, Significance, vol 12 no. 2 (2015), pp. 40-42 [10.1111/j.1740-9713.2015.00816.x] [abs].
- Aganj, I; Sapiro, G; Harel, N, Q-Space Modeling in Diffusion-Weighted MRI, vol 1 (2015), pp. 257-263 [10.1016/B978-0-12-397025-1.00293-1] [abs].
- Kim, J; Duchin, Y; Sapiro, G; Vitek, J; Harel, N, Clinical subthalamic nucleus prediction from high-field brain MRI, Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro. IEEE International Symposium on Biomedical Imaging, vol 2015-July (2015), pp. 1264-1267 [10.1109/ISBI.2015.7164104] [abs].
- Yang, J; Liao, X; Yuan, X; Llull, P; Brady, DJ; Sapiro, G; Carin, L, Compressive sensing by learning a Gaussian mixture model from measurements., IEEE Transactions on Image Processing, vol 24 no. 1 (2015), pp. 106-119 [abs].