Ryan Tibshirani

Ryan J. Tibshirani
Born (1985-12-15) December 15, 1985
Toronto, Canada
Alma materStanford University (BS, PhD)
Known forGeneralized lasso, trend filtering, selective inference, conformal prediction
AwardsCOPSS Presidents' Award (2023); Mortimer Spiegelman Award (2022); Fellow of the Institute of Mathematical Statistics (2022); NSF CAREER Award (2016)
Scientific career
FieldsStatistics, machine learning
WorkplacesUniversity of California, Berkeley
ThesisThe Solution Path of the Generalized Lasso (2011)
Jonathan Taylor
Websitewww.stat.berkeley.edu/~ryantibs/

Ryan Joseph Tibshirani (born December 15, 1985) is a professor and chair of the Department of Statistics at the University of California, Berkeley.[1] His work spans high-dimensional statistics, nonparametric estimation, distribution-free inference, convex optimization, and epidemic tracking and forecasting.[2][3][4]

Early life and education

Tibshirani was born on December 15, 1985 in Toronto, Canada. He earned a B.S. in Mathematics from Stanford University in 2007 and a Ph.D. in Statistics from Stanford in 2011; his dissertation, The Solution Path of the Generalized Lasso, was advised by Jonathan Taylor.[5][6]

Career

From 2011 to 2022, Tibshirani was a faculty member in the Department of Statistics and Department of Machine Learning at Carnegie Mellon University (CMU).[7] He joined UC Berkeley in 2022 and became department chair effective July 1, 2025.[1]

Tibshirani is a principal investigator with the Delphi Research Group, which develops epidemic tracking and forecasting systems in collaboration with the Centers for Disease Control and Prevention (CDC), as well as other partners.[8][9][10][11]

In 2023, he became Editor-in-Chief of Foundations and Trends in Machine Learning, taking over from founding Editor Michael I. Jordan.[12] In 2024, he became founding co-Editor-in-Chief of Foundations and Trends in Statistics with Rina Foygel Barber.[13]

Research

Tibshirani’s research focuses on methodology and theory for high-dimensional and nonparametric problems, often connecting statistical inference with convex optimization.[2][3] He has made important contributions to regularization and sparsity methods, including the lasso, generalized lasso, and trend filtering, developing both theoretical guarantees and efficient algorithms.[14][15] He has also contributed to selective inference, to distribution-free predictive inference (conformal prediction), and to epidemic modeling and forecasting.[16][17]

Awards and honors

Personal life

Ryan Tibshirani is the son of statistician Robert Tibshirani, with older brother Charlie Tibshirani, and younger sister Julie Tibshirani who is a co-creator generalized random forests.[29] He is married to Jessica Tibshirani (née Issler) and they have two children.[30]

Selected publications

  • Tibshirani, Ryan J.; Taylor, Jonathan (2011). "The solution path of the generalized lasso". Annals of Statistics. 39 (3): 1335–1371. arXiv:1005.1971. doi:10.1214/11-AOS878.
  • Tibshirani, Ryan J. (2014). "Adaptive piecewise polynomial estimation via trend filtering". Annals of Statistics. 42 (1): 285–323. arXiv:1304.2986. doi:10.1214/13-AOS1189.
  • Lockhart, Richard; Taylor, Jonathan; Tibshirani, Ryan J.; Tibshirani, Robert (2014). "The solution path of the generalized lasso". Annals of Statistics. 42 (2): 413–468. arXiv:1005.1971. doi:10.1214/11-AOS878.
  • Wang, Yu-Xiang; Smola, Alex J.; Tibshirani, Ryan J. (2016). "Trend filtering on graphs". Journal of Machine Learning Research. 17 (105): 1–41.
  • Lei, Jing; G'Sell, Max; Rinaldo, Alessandro; Tibshirani, Ryan J.; Wasserman, Larry (2018). "Distribution-free predictive inference for regression". Journal of the American Statistical Association. 113 (523): 1094–1111. doi:10.1080/01621459.2017.1307116.
  • Barber, Rina Foygel; Candès, Emmanuel J.; Ramdas, Aaditya; Tibshirani, Ryan J. (2023). "Conformal prediction beyond exchangeability". Annals of Statistics. 51 (2): 816–845. doi:10.1214/23-AOS2276.

References

  1. 1 2 "Tibshirani Named Chair". UC Berkeley Statistics. June 18, 2025. Retrieved August 8, 2025.
  2. 1 2 3 "Ryan Tibshirani wins the prestigious 2023 COPSS Presidents' Award". Institute of Mathematical Statistics. August 31, 2023. Retrieved August 8, 2025.
  3. 1 2 "Ryan Tibshirani, Berkeley professor and Amazon Scholar, wins COPSS Presidents' Award". Amazon Science. September 2023. Retrieved August 8, 2025.
  4. ↑ "Ryan Tibshirani". UC Berkeley Statistics. Retrieved August 8, 2025.
  5. ↑ "Ryan Tibshirani". Stanford Department of Statistics. Retrieved August 8, 2025.
  6. ↑ Tibshirani, Ryan J. (2011). The Solution Path of the Generalized Lasso (PDF) (PhD thesis). Stanford University.
  7. ↑ "Ryan Tibshirani (archived CMU profile)". Carnegie Mellon University. Retrieved August 8, 2025.
  8. ↑ "Delphi Group Awarded $17.5 million from CDC". UC Berkeley Statistics. November 15, 2023. Retrieved August 8, 2025.
  9. ↑ "Unveil interactive COVID-19 tracking at county level". Medical Xpress. April 17, 2020. Retrieved August 8, 2025.
  10. ↑ "Facebook and Google share data to forecast coronavirus". MIT Technology Review. April 9, 2020. Retrieved August 8, 2025.
  11. ↑ Rosenfeld, Roni; Tibshirani, Ryan J. (2021). "Epidemic tracking and forecasting: Lessons learned from a tumultuous year". Proceedings of the National Academy of Sciences. 118 (26). doi:10.1073/pnas.2111456118. PMC 8713795. PMID 34903658.
  12. ↑ "Foundations and Trends in Machine Learning — Editorial Board". Emerald Publishers. Retrieved June 14, 2026.
  13. ↑ "Foundations and Trends in Statistics — Editorial Board". Emerald Publishers. Retrieved June 14, 2026.
  14. ↑ Tibshirani, Ryan J.; Taylor, Jonathan (2011). "The solution path of the generalized lasso". Annals of Statistics. 39 (3): 1335–1371. arXiv:1005.1971. doi:10.1214/11-AOS878.
  15. ↑ Tibshirani, Ryan J. (2014). "Adaptive piecewise polynomial estimation via trend filtering". Annals of Statistics. 42 (1): 285–323. arXiv:1304.2986. doi:10.1214/13-AOS1189.
  16. ↑ Lockhart, Richard; Taylor, Jonathan; Tibshirani, Ryan J.; Tibshirani, Robert (2014). "The solution path of the generalized lasso". Annals of Statistics. 42 (2): 413–468. arXiv:1005.1971. doi:10.1214/11-AOS878.
  17. ↑ Lei, Jing; G'Sell, Max; Rinaldo, Alessandro; Tibshirani, Ryan J.; Wasserman, Larry (2018). "Distribution-free predictive inference for regression". Journal of the American Statistical Association. 113 (523): 1094–1111. doi:10.1080/01621459.2017.1307116.
  18. ↑ "Presidents' Award". Committee of Presidents of Statistical Societies. Retrieved August 8, 2025.
  19. ↑ "Mortimer Spiegelman Award - Past Winners". APHA Applied Public Health Statistics Section. Retrieved August 8, 2025.
  20. ↑ "Ryan Tibshirani Recipient of the 2022 Mortimer Spiegelman Award". UC Berkeley Statistics. August 30, 2022. Retrieved August 8, 2025.
  21. ↑ "2022 IMS Fellows Announced". Institute of Mathematical Statistics. April 22, 2022. Retrieved August 8, 2025.
  22. ↑ "Rinaldo and Tibshirani Selected as 2022 IMS Fellows". Carnegie Mellon University. April 25, 2022. Retrieved August 8, 2025.
  23. ↑ "2022 Award Winners". AAPOR. December 7, 2022. Retrieved August 8, 2025.
  24. ↑ "Delphi Group, University of Maryland, Meta Honored for AAPOR Awards". CMU School of Computer Science. April 20, 2022. Retrieved August 8, 2025.
  25. ↑ "Delphi Research Group, Collaborators Honored for COVIDcast". Carnegie Mellon University. May 12, 2021. Retrieved August 8, 2025.
  26. ↑ "2021 SPAIG Award" (PDF). Amstat News. October 2021. Retrieved August 8, 2025.
  27. ↑ "Teaching Innovation Award - Past Recipients". Carnegie Mellon University. Retrieved August 8, 2025.
  28. ↑ "Two CMU Statistics Professors Earn NSF CAREER Awards". Carnegie Mellon University. February 22, 2016. Retrieved August 8, 2025.
  29. ↑ "Generalized Random Forest". Retrieved August 9, 2025.
  30. ↑ "Ryan Tibshirani - Other". UC Berkeley. Retrieved August 9, 2025.
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