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Jacob Bien

  • Professor of Data Sciences and Operations

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, a three-year NSF grant on high-dimensional covariance estimation, an NIH R01 grant on methods for multi-view data, and grants from the Simons Foundation on developing new statistical methodology for oceanography. He is a fellow of the Institute of Mathematical Statistics and serves as an associate editor of the Journal of the American Statistical Association and the Journal of the Royal Statistical Society (Series B); he was previously an associate editor for Biometrika, the Journal of Computational and Graphical Statistics, and Biostatistics. Before joining USC, he was an assistant professor at Cornell.

Jacob Bien

Areas of Expertise

Analytics
Machine Learning
Optimization
Statistical Inference
Statistics

Departments

Data Sciences + Operations

RESEARCH + PUBLICATIONS