Trevor Hastie

Trevor John Hastie
Born (1953-06-27) 27 June 1953
South Africa
Nationality American
Fields Statistical learning, Data mining, bioinformatics
Institutions AT&T Bell Laboratories
Stanford University
Alma mater Rhodes University
University of Cape Town
Stanford University
Doctoral advisor Werner Stuetzle
Spouse Lynda Hastie

Trevor John Hastie (born 27 June 1953) is an American statistician and computer scientist. He is currently serving as the John A. Overdeck Professor of Mathematical Sciences and Professor of Statistics at the Stanford University.[1] Hastie is known for his contributions to applied statistics, especially in the field of machine learning, data mining, and bioinformatics. He has authored several popular books in statistical learning, including The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Hastie has been listed as an ISI Highly Cited Author in Mathematics by the ISI Web of Knowledge.

Education and career

Hastie was born on 27 June 1953 in South Africa.[2] He received his B.S. in statistics from the Rhodes University in 1976 and Master's degree from University of Cape Town in 1979. Hastie joined the doctoral program at Stanford University in 1980 and received his Ph.D. in 1984 under the supervision of Werner Stuetzle. His dissertation was "Principal Curves and Surfaces".[2]

Hastie began his professional career in 1977 with the South African Medical Research Council. After receiving his Master's degree in 1979, he spent a year interning at the London School of Hygiene & Tropical Medicine, the Johnson Space Center in Houston, and the Biomath department at Oxford University. After receiving his doctoral degree from Stanford, Hastie returned to South Africa to work with his former employer South African Medical Research Council. He returned to United States in 1986 and joined the AT&T Bell Laboratories in Murray Hill, New Jersey and remained there for nine years. He joined Stanford University in 1994 as Associate Professor in Statistics and Biostatistics. He was promoted to full Professor in 1999. During the period 2006-2009, he was the Chair of Department of Statistics at Stanford University. In 2013 he was named the John A. Overdeck Professor of Mathematical Sciences.

Awards and honors

Hastie is a Fellow of the Royal Statistical Society since 1979. He is also an elected Fellow of several professional and scholarly societies, including the Institute of Mathematical Statistics,[3] the American Statistical Association,[4] and the South African Statistical Society. He is a recipient of 'Myrto Lefkopolou Distinguished Lectureship' award of Biostatistics Department at the Harvard School of Public Health.[5]

Publications

Hastie is a prolific author of scientific works on various topics in applied statistics, including statistical learning, data mining, statistical computing, and bioinformatics. He along with his collaborators has authored about 125 scientific articles. Many of Hastie's scientific articles were coauthored by his longtime collaborator, Robert Tibshirani. Hastie has been listed as an ISI Highly Cited Author in Mathematics by the ISI Web of Knowledge.[6] He has coauthored the following books:

References

  1. "Trevor J. Hastie, Department of Statistics". Stanford University. Retrieved 8 April 2012.
  2. 1 2 "Trevor John Hastie" (PDF). Retrieved 8 April 2012.
  3. "Honored IMS Fellows". Institute of Mathematical Statistics. Retrieved 8 April 2012.
  4. "Fellows of the ASA". American Statistical Association. Retrieved 8 April 2012.
  5. "Myrto Lefkopoulou Distinguished Lecturership". Department of Biostatistics, Harvard School of Public Health. Retrieved 8 April 2012.
  6. "H - Research Analytics". Thomson Reuters. Retrieved 8 April 2012.
  7. Hastie, Trevor; Tibshirani, Robert; Friedman, Jerome H. "The Elements of Statistical Learning". Retrieved 15 June 2012.
  8. James, Gareth; Witten, Daniela; Hastie, Trevor; Tibshirani, Robert. "An Introduction to Statistical Learning with Applications in R". Retrieved 3 July 2016.
  9. Hastie, Trevor; Tibshirani, Robert; Wainwright, Martin. "Statistical Learning with Sparsity: the Lasso and Generalizations". Retrieved 3 July 2016.
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