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William S. Cleveland
William S. Cleveland (born 1943) is an American computer scientist and Professor of Statistics and Professor of Computer Science at Purdue University, known for his work on data visualization, particularly on nonparametric regression〔Armitage, Peter, Geoffrey Berry, and John NS Matthews. Statistical methods in medical research. John Wiley & Sons, 2008.〕 and local regression.〔Venables, William N., and Brian D. Ripley. ''Modern applied statistics with S.'' Springer Science & Business Media, 2002.〕
== Biography ==
Cleveland obtained his AB in Mathematics mid 1960s from Princeton University, where he graduated under William Feller. For his PhD studies in Statistics he moved to Yale University, where he graduated under Leonard Jimmie Savage.〔(William S. Cleveland, CV ), at stat.purdue.edu. Accessed 10-04-2015.〕
After graduation Cleveland started at Bell Labs, where he was staff member of the Statistics Research Department and Department Head for 12 years. Eventually he moved to the Purdue University, where he became Professor of Statistics and Courtesy Professor of Computer Science.
His research interests are in the fields of "data visualization, computer networking, machine learning, data mining, time series, statistical modeling, visual perception, environmental science, and seasonal adjustment."〔(William S. Cleveland: Bio ), at stat.purdue.edu. Accessed 10-04-2015.〕
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