Sandrine Dudoit

Timeline

1. By 1999

   Mathematics and a statistics doctorate

   Born in Montreal, she grows up in Canada and France. She earns mathematics degrees at Carleton University: a BSc in 1992 and a master's in 1994. In 1999, she completes a statistics PhD at UC Berkeley under Terry Speed.

2. 2001–2006

   From Stanford to Berkeley

   After postdoctoral research with Patrick O. Brown at Stanford University, she joins the Division of Biostatistics in UC Berkeley's School of Public Health as an assistant professor in 2001. She adds a joint appointment in Berkeley's Department of Statistics in 2006.

3. 2001

   Co-founding Bioconductor

   In 2001, she co-founds the Bioconductor Project, an international effort to build open-source software for analysing biomedical and genomic data.

4. 2005

   A book on Bioconductor

   In 2005, she co-edits Bioinformatics and Computational Biology Solutions Using R and Bioconductor. Springer publishes the book in its Statistics for Biology and Health series.

5. 2008

   Multiple testing for genomics

   In 2008, she coauthors Multiple Testing Procedures with Applications to Genomics with M. J. van der Laan. Springer publishes the book in its Series in Statistics.

6. 2018

   Slingshot traces cell development

   In 2018, she coauthors the Slingshot paper with Kelly Street and colleagues in BMC Genomics. The method infers multiple developmental lineages from single-cell gene expression data and orders cells along branching paths.

7. July 2019–June 2022

   Chair of Berkeley Statistics

   From July 2019 to June 2022, she serves as chair of UC Berkeley's Department of Statistics.

8. 2021

   An IMS fellowship

   In 2021, she becomes a Fellow of the Institute of Mathematical Statistics.

9. 2025

   An IMS Medallion Award

   In 2025, she receives a Medallion Award from the Institute of Mathematical Statistics.

10. As of October 2026

    Professor and executive associate dean

    As of October 2026, she is a professor in UC Berkeley's Department of Statistics and Division of Biostatistics in the School of Public Health. She also serves as executive associate dean of the College of Computing, Data Science, and Society. Her research develops statistical learning methods and software for genomic data and precision health, including clustering, dimensionality reduction, prediction, and causal inference.