Toby Berger , an influential leader of information theory whose contributions to rate distortion and source coding have impacted how audio and video files are compressed for efficient transmission and viewing over the Internet, was honored by IEEE with the 2011 IEEE Richard W. Hamming Medal.
The medal, sponsored by Qualcomm, Inc., recognizes Berger for contributions to Information Theory, including source coding and its applications. The medal was presented on 20 August 2011 at the IEEE Honors Ceremony in San Francisco, Calif.
Among many important contributions to advancing information theory, Berger is most known for his work on rate distortion theory and source coding. Rate distortion theory, first addressed by Claude Shannon in 1948, concerns the methods for compressing and communicating data without causing too much degradation of the content. The goal is to determine the minimum amount of data that can be communicated so that the signal can be reconstructed at the receiver with tolerable distortion. These methods make possible the efficient transmission and playing of audio, photo and video files over the Internet and mobile devices.
Berger was the first to extend Shannon’s lossy coding theorem to abstract-alphabet sources with memory in 1968. Lossy data compression allows for some loss of data in return for higher compression. It is suitable for audio and video files where reproduction of the content does not need to be perfect due to the effects of human perception on what is acceptable. Berger’s pioneering work was the forerunner of the widely adopted JPEG and MPEG standards for picture and video files. The structures of today’s video coding standards resemble the structures Berger described in 1970. His book, “Rate Distortion Theory: A Mathematical Basis for Data Compression” (Prentice Hall, 1971) became the best reference on the topic and is still an important resource today.
Berger is also one of the pioneers of multiuser source coding, which deals with the challenges of handling the transfer of information from one to many. Building on his rate-distortion work, Berger helped define the framework and future directions for distributed source coding and distributed lossy coding. He defined fundamental concepts including strong typicality and the Markov lemma for distributed source coding and network information theory. Berger’s introduction of the “CEO problem” for multiterminal source coding during the late 1990s is considered one of the most important contributions in the history of distributed coding.
Berger’s more recent interests include building bridges between information theory and biological systems for an interdisciplinary area called “neuroinformation theory.” Combining information theory, neuroscience and mathematical statistics, Berger’s goal is to quantify how real neurons compute and communicate. This area holds promise as the basis for a theory of energy-efficient computation and communication that is analog instead of digital.
An IEEE Life Fellow, Berger is also a member of the U.S. National Academy of Engineering. His honors include the IEEE Third Millennium Medal, the IEEE Information Theory Society’s Shannon Award and the IEEE Leon K. Kirchmayer Graduate Teaching Award. He received his bachelor’s degree from Yale University, New Haven, Conn., and master’s and doctorate degrees from Harvard University, Cambridge, Mass. Berger is the Irwin and Joan Jacobs Professor of Engineering, Emeritus, at Cornell University, Ithaca, N.Y., and professor of electrical and computer engineering at the University of Virginia, Charlottesville.