Jacob Bien
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Associate Professor of Data Sciences and Operations (Statistics group) |
I work on problems in statistical machine learning and in particular the development of novel methods that balance flexibility and interpretability for analyzing complex data. My goal is to develop methods that are of direct use to scientists and others with large datasets. A particular interest of mine is in using convex optimization to tackle the challenges of high-dimensional data. When I develop a new method, I take a broad approach to its study, considering practical, computational, and theoretical aspects.
Excited to share a new way to write R packages! Use the litr R package to define an entire R package in a single R markdown file. The R package is created when you knit the Rmd file. For larger packages, you can write a bookdown that defines the package.
Education
PhD in Statistics, Stanford University, 2012, advised by Rob Tibshirani.
MS in Statistics, Stanford University, 2007.
BS in Physics, Stanford University (secondary major in Mathematics), 2006.
Other positions
Associate Editor, Journal of the American Statistical Association
Associate Editor, Journal of the Royal Statistical Society, Series B (Statistical Methodology)
Member of board of directors of Wonderfest, the “Bay Area Beacon of Science”
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