Robert Tibshirani

Timeline

1. 1956–1984

   Education in statistics

   Born in Niagara Falls, Ontario, in 1956, he earns a BMath in statistics and computer science at the University of Waterloo in 1979 and an MSc in statistics at the University of Toronto in 1980. He completes a statistics PhD at Stanford in 1984 under Bradley Efron.

2. 1985–1994

   Toronto faculty and early books

   He joins the University of Toronto in 1985 as an assistant professor in the Departments of Statistics and Preventive Medicine and Biostatistics, and becomes a full professor in Public Health Sciences and Statistics in 1994. With Trevor Hastie, he publishes Generalized Additive Models in 1990; with Bradley Efron, he publishes An Introduction to the Bootstrap in 1993.

3. 1996

   Regression with the lasso

   His 1996 paper, ‘Regression Shrinkage and Selection via the Lasso’, introduces a regression method that selects variables and regularizes models to improve prediction and interpretation. He receives the COPSS Presidents’ Award in 1996.

4. 1998

   Professor at Stanford

   In 1998, he moves from Toronto to Stanford as a professor in the Departments of Health Research and Policy and Statistics.

5. 2001

   The Elements of Statistical Learning

   With Trevor Hastie and Jerome Friedman, he coauthors The Elements of Statistical Learning in 2001, a book on statistical learning and machine learning.

6. 2012

   Academy membership and Gold Medal

   He is elected to the US National Academy of Sciences in 2012. The Statistical Society of Canada awards him its Gold Medal in 2012 for work that includes statistical learning, high-dimensional data analysis, and applications in genetics and medicine.

7. 2013

   An Introduction to Statistical Learning

   In 2013, he coauthors An Introduction to Statistical Learning with Gareth James, Daniela Witten, and Trevor Hastie. The book introduces statistical learning methods with applications in R and practical labs.

8. 2019

   Election to the Royal Society

   He is elected a Fellow of the Royal Society in 2019. His statistical methods include lasso regression, generalized additive models, and Significance Analysis of Microarrays.

9. 2021–2024

   Statistical research awards

   In 2021, he receives the ISI Founders of Statistics Prize for his 1996 lasso paper. He receives the COPSS Distinguished Achievement Award and Lectureship in 2024 for contributions to statistics and machine learning, textbooks, and mentoring.

10. 2025–2026

    Sparse regression at Stanford

    With Sourav Chatterjee and Trevor Hastie, he introduces uniLasso in 2025, a two-stage method for sparse regression. In 2026, he coauthors work that adapts uniLasso to genetic risk prediction using UK Biobank data. He continues as a professor in Stanford’s Departments of Biomedical Data Science and Statistics, appointments that begin in 2015, with research in biology, genomics, medicine, and industry.