Michael Elad is a prominent researcher in the field of applied mathematics, particularly known for his work in signal and image processing, machine learning, and inverse problems. He has contributed significantly to areas such as compressive sensing, statistical imaging, and image restoration. His research often explores mathematical frameworks and algorithms to solve real-world problems in imaging and data analysis, making him a well-respected figure in the mathematical and engineering communities.
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