Jacob Bien

Assistant Professor of Data Sciences and Operations
Room / Office

PhD, Statistics, Stanford (advisor: Robert Tibshirani); BS, Physics, Stanford

Jacob Bien's research focuses on statistical machine learning and in particular the development of novel methods that balance flexibility and interpretability for analyzing complex data. He combines ideas from convex optimization and statistics to develop methods that are of direct use to scientists and others with large datasets. His work has been supported by an NSF CAREER award and a three-year NSF grant on high-dimensional covariance estimation. He serves as an associate editor of Biometrika and Biostatistics. Before joining USC, he was an assistant professor at Cornell.

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Bien, Jacob.,Gaynanova, Irina.,Lederer, Johannes.,M\"uller, Christian L. () "Non-convex global minimization and false discovery rate control for the TREX", Journal of Computational and Graphical Statistics.
Nicholson, William.,Bien, Jacob.,Matteson, David. () "Hierarchical vector autoregression", arXiv preprint arXiv:1412.5250.