| Michael Elad | |
| Birth Date: | 10 December 1963 |
| Birth Place: | Haifa, Israel |
| Nationality: | Israel |
| Fields: | Engineering, Computer Science, Mathematics, Statistics |
| Workplaces: | Technion Stanford University |
| Alma Mater: | Technion |
| Doctoral Advisor: | Arie Feuer |
| Doctoral Students: | Michal Aharon |
| Known For: | Sparse Representations, K-SVD, Image Super-Resolution, Diffusion Models |
Michael Elad (born December 10, 1963) is an Israeli computer scientist who is a professor of Computer Science at the Technion - Israel Institute of Technology. His work includes contributions in the fields of sparse representations and generative AI, and deployment of these ideas to algorithms and applications in signal processing, image processing and machine learning.
Elad holds a B.Sc. (1986), M.Sc. (1988) and D.Sc. (1997) in electrical engineering from the Technion - Israel Institute of Technology. His M.Sc., under the guidance of David Malah, focused on video compression algorithms; and his D.Sc. on super-resolution algorithms for image sequences, was guided by Arie Feuer.
After several years (1997–2001) in industrial research in Hewlett-Packard Lab Israel and in Jigami, Elad took a research associate position at Stanford University from 2001 to 2003, working closely with Gene Golub (CS-Stanford), Peyman Milanfar (EE-UCSC) and David Donoho (Statistics-Stanford).
In 2003, Elad assumed a tenure-track faculty position in the Technion's computer science department. He was tenured and promoted to associate professorship in 2007, and promoted to full-professorship in 2010. The following is a list of is editorial activities during his academic career:
Elad works in the fields of signal processing, image processing and machine learning, specializing in particular on inverse problems, sparse representations and generative AI. Elad has authored hundreds of technical publications in these fields. Among these, he is the creator of the K-SVD algorithm,[1] together with Michal Aharon and Bruckstein, and he is also the author of the 2010 book[2] "Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing".
In 2017, Elad and Yaniv Romano (his PhD student) created a specialized MOOC on sparse representation theory, given under edX.
During the years 2015-2018, Elad headed the Rothschild-Technion Program for Excellence]. This is an undergraduate program at the Technion, meant for exceptional students with emphasis on tailored and challenging study tracks.