Michael Elad holds a B.Sc. (1986), M.Sc. (1988) and D.Sc. (1997) in Electrical Engineering from the Technion, Israel Institute of Technology. After several years of industrial research, Michael served as a research associate at Stanford University during 2001-2003. Since 2003 he holds a permanent faculty position in the Computer-Science department at the Technion.

Michael Elad works in the fields of signal and image processing and machine learning, specializing in particular on inverse problems, sparse representations and deep learning. Prof. Elad has authored hundreds of technical publications in leading venues, many of which have led to exceptionally high impact. He is the author of the 2010’s book “Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing”, which is a leading publication in this field.