Yoav Benjamini
Yoav Benjamini
Born	(1949-01-05) 5 January 1949 (age 75) Israel
Alma mater	Princeton University
Known for	False discovery rate
Awards	Israel Prize (2021)
Scientific career
Fields	Statistics
Institutions	Tel Aviv University
Thesis	Is the t-test conservative when the parent distribution is long tailed? (1981)
Doctoral advisor	Peter Bloomfield

Yoav Benjamini (Hebrew: יואב בנימיני; born 5 January 1949) is an Israeli statistician best known for development (with Yosef Hochberg) of the "false discovery rate" criterion. He is currently The Nathan and Lily Silver Professor of Applied Statistics at Tel Aviv University.

Early life

Yoav graduated high school from the Hebrew Reali School in Haifa in 1966 and later studied mathematics and physics at the Hebrew University of Jerusalem, Israel graduating in 1973. His master's degree in mathematics is from the same university in 1976. In 1981, he received his PhD in statistics from Princeton University, US.^[1]

Scientific fields of interest

Benjamini's scientific work combines theoretical research in statistical methodology with applied research that involves complex problems with massive data. The methodological work is on selective and simultaneous inference (multiple comparisons), as well as on general methods for data analysis, data mining, and data visualization. His research citations (from Google Scholar) exceeds 100,000.^[2]

Honors and awards

• 2012 Israel Prize recipient in statistics^[3]
• 2020 elected to the National Academy of Sciences (NAS), US^[4][5][6]

Publications

• 1983: "Is the T-test really conservative when the parent distribution is long-tailed", Journal of the American Statistical Association
• 1986: "Observational rainfall – runoff analysis for estimating effects of cloud seeding on water resources in Northern Israel", Journal of Hydrology (with Y. Harpaz)
• 1988: "Opening the box of a boxplot", The American Statistician
• 1990: "More powerful procedures for multiple significance testing", Statistics in Medicine (with Y. Hochberg)
• 1995: "Controlling the False Discovery Rate: a practical and powerful approach to multiple testing", Journal of the Royal Statistical Society, Series B (with Y. Hochberg)
• 1998: "Confidence intervals with more power to determine the sign: two ends constrain the means", Journal of the American Statistical Association (with Y. Hochberg & PB. Stark)
• 2000: "The adaptive control of the false discovery rate in multiple comparison problems", The Journal of Educational and Behavioral Statistics (with Y. Hochberg)
• 2001: The control of the False Discovery Rate in multiple testing under dependency, Annals of Statistics (with D. Yekutieli)
• 2002: John Tukey’s contributions to multiple comparisons, Annals of Statistics, (with H. Braun)
• 2003: Identifying Differentially Expressed Genes Using False Discovery Rate Controlling Procedures, Bioinformatics (with A. Reiner & D. Yekutieli)
• 2005: Genotype-environment interactions in mouse behavior: A way out of the problem, Proceedings of the National Academy of Sciences (with N. Kafkafi, A. Sakov & others)
• 2005: False discovery rate controlling confidence intervals for selected parameters, Journal of the American Statistical Association (with Y. Yekutieli
• 2006: Adapting to unknown sparsity by controlling the false discovery rate, Annals of Statistics (with: F. Abramovich, D. Donoho & IM. Johnstone)
• 2006: Adaptive linear step-up procedures that control the false discovery rate, Biometrika (with A.M. Krieger & D. Yekutieli)
• 2008: Screening for partial conjunction hypotheses. Biometrics (with R. Heller)
• 2011: Quantifying the buildup in extent and complexity of behavior – the case of free exploration in mice, Proceedings of the National Academy of Sciences (with E. Fonio, T. Galili and others)