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Martin Vetterli is a renowned professor in the field of signal processing and communications, affiliated with EPFL. He has made significant contributions to the theory of wavelets, sampling theory, and inverse problems, focusing on sparse representations and their applications in various domains including high-quality art rendering and sensor networks. His research has garnered funding from prestigious organizations such as the Swiss National Science Foundation and the European Research Council, as well as industrial partners like Qualcomm and Google. Vetterli's work is recognized globally, as evidenced by numerous awards, including the IEEE Jack S. Kilby Signal Processing Medal and multiple IEEE and EURASIP Technical Achievement Awards. He has published extensively, with seminal papers addressing topics such as multiresolution image representation, Gaussian relay networks, and adaptive wavelet thresholding. Vetterli is also deeply involved in online education, contributing to courses in digital signal processing.
École Polytechnique Fédérale de Lausanne • Lausanne, Switzerland
Teaching and conducting research in signal processing and communications, focusing on wavelets and other advanced algorithms.
Standard requirements for Engineering and Basic Science Master's programs. Architecture requires an additional portfolio.