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Alon Orlitsky Named 2021 Claude E. Shannon Award Winner
Alon Orlitsky wins the Claude E. Shannon award for consistent and profound contributions to the field of information theory. He will deliver his Shannon lecture at ISIT 2021.
Jun 25, 2020
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Alon Orlitsky  has been named the recipient of the 2021 Claude E. Shannon Award. 

Orlitsky (S’83–M’84–SM’00–F’06) received B.Sc. degrees in Mathematics and Electrical Engineering from Ben Gurion University in 1980 and 1981, and M.Sc. and Ph.D. degrees in Electrical Engineering from Stanford University in 1982 and 1986.,From 1986 to 1996 he was with the Communications Analysis Research Department of Bell Laboratories. He spent the following year as a quantitative analyst at D.E. Shaw and Company, an investment firm in New York City. In 1997 he joined the University of California San Diego, where he is currently a professor of Electrical and Computer Engineering and of Computer Science and Engineering. His research concerns information theory, statistical modeling, and machine learning.

From 2011 to 2014 Alon directed UCSD’s Center for Wireless Communications, and since 2006 he has directed the Information Theory and Applications Center. He was the president of the Information Theory Society in 2016. He has co-organized numerous programs on information theory, machine learning, and statistics, including the Information Theory and Applications Workshop that he started in 2006 and has helped organize since.

Alon is a recipient of the 1981 ITT International Fellowship and the 1992 Â鶹´«Ã½Ó³»­ W.R.G. Baker Paper Award, and co-recipient of the 2006 Information Theory Society Paper Award and the 2016 NIPS Paper Award. He co-authored two papers for which his students received student-paper awards: the 2003 Capocelli Prize and the 2010 ISIT Student Paper Award. He is a fellow of the Â鶹´«Ã½Ó³»­, and holds the Qucalcomm Chair for Information Theory and its Applications at UCSD.

The Claude E. Shannon Award has been instituted to honor consistent and profound contributions to the field of information theory.