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Trevor Hastie (Professor)

Trevor Hastie (650) 725-2231
hastie
I'm-not-a-bot
@stanford
Personal bio
Trevor Hastie eas born in South Africa in 1953, and was educated at Rhodes University (B.Sc hons) and the University of Cape Town (M.Sc). He worked at the Institute for Biostatistics at the South African Medical Research Council for three years, before leaving for the USA to earn a Ph.D in Statistics from Stanford University in 1984. He returned to the MRC for one year, and then joined the research staff at AT&T Bell Laboratories in Murray Hill, NJ from 1986-1994. He joined the faculty of the Department of Statistics at Stanford University in 1994 as Professor of Statistics and Biostatistics. His main research contributions have been in the field of applied regression and classification, and he has written two books in this area: Generalized Additive Models (with R. Tibshirani, Chapman and Hall, 1991), and Elements of Statistical Learning (with R. Tibshirani and J. Friedman, Springer 2001; 2nd edition 2009). He has also made contributions in statistical computing, co-editing (with J. Chambers) a large software library of modeling tools in the S language (Statistical Models in S, Wadsworth, 1992), which form the basis for much of the statistical modeling in R. His current research focuses on applied problems in biology and genomics, medicine and industry, in particular data mining, prediction and classification problems.

Currently teaching
STATS 305C: Applied Statistics III (Spring)
BIOMEDIN 370: Medical Scholars Research (Autumn, Winter, Spring, Summer)
BIOMEDIN 299: Directed Reading and Research (Autumn, Winter, Spring, Summer)
STATS 398: Industrial Research for Statisticians (Autumn, Winter, Spring, Summer)
CME 400: Ph.D. Research (Autumn, Winter)
HRP 370: Medical Scholars Research (Autumn, Winter, Spring, Summer)
STATS 399: Research (Autumn, Winter, Spring, Summer)
BIOMEDIN 290: Biomedical Informatics Teaching Methods (Autumn, Winter, Spring, Summer)
BIODS 299: Directed Reading and Research (Autumn, Winter, Spring, Summer)
STATS 299: Independent Study (Summer)
STATS 298: Industrial Research for Statisticians (Winter)
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