After his dissertation, he was an assistant and associate professor in electrical engineering at Columbia University in New York, and in 1993, he became an associate and then full professor at the Department of Electrical Engineering and Computer Sciences at the University of California at Berkeley in California.
In 1995, he joined EPFL as a full-time professor. He held several positions there, including chair of communication systems and founding director of the National Competence Center in Research on Mobile Information and Communication systems (NCCR-MICS).
From 2004 to 2011, he was vice president of EPFL for international affairs and, from 2011 to 2012, he was the dean of the School of Computer and Communications Sciences at EPFL.
In 2015, he was elected to the United States National Academy of Engineering for his contributions to the development of time-frequency representations and algorithms in multimedia signal processing and communications.[3]
He is also responsible for developing, publishing and maintaining an extensive massive open online course on the basics of digital signal processing. The course is a collaboration effort between him and his colleague, Paolo Prandoni. The course was first offered in February 2013 on Coursera and has been offered every year on the site since then. Each session runs for 10 weeks.[5][6]
At the core of his laboratory's current research is mathematical signal processing, that is, the set of tools and algorithms from applied harmonic analysis that are central to signal processing. These include representations for signals (Fourier, wavelets, frames), sampling theory, and sparse representations.
A main application of signal processing is in communications and sensor networks. In addition to important classic topics like channel estimation and equalization, multiuser systems like sensor networks are of great interest. This leads to distributed compression, sampling, and modeling of physical phenomena.
The area of audio processing and digital acoustics deals with multi-channel acquisition, processing and rendering of audio signals. This includes questions of sound field sampling, synthesis and perception.
Inverse problems and tomography are key signal processing tasks where state of the art techniques have high potential impact. In particular, the project on ultrasound tomography intends to solve a long-standing quest for a safe and affordable breast cancer screening method.
In the area of image/video processing and applications, his research has on-going projects in image acquisition, image representations, and super-resolution imaging. Applications include image annotation and augmented reality for mobile devices.
The eFacsimile research project, sponsored by Google, is focused on the research and development of a new acquisition, representation and rendering paradigm for the high-quality reproduction of artwork.
The research of Martin Vetterli has led to about 150 journal papers and resulted also in about two dozen patents that led to technology transfers to high-tech companies and the creation of several start-ups.[8]
Martin Vetterli is a co-author of the book Wavelets and Subband Coding (Prentice-Hall, 1995).[9] In 2008, Vetterli authored with Paolo Prandoni a free textbook Signal Processing for Communications.[10]
In 2014, another book with the title Foundations of Signal Processing (coauthored by Jelena Kovačević and Vivek Goyal) was also published freely accessible.[11]
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