Bin Yu

Scientific Advisor, UC Berkeley

Bin Yu is Chancellor's Distinguished Professor and Class of 1936 Second Chair
in the departments of statistics and EECS at UC Berkeley. She leads the Yu Group which consists of students and postdocs from Statistics and EECS. She was formally trained as a statistician, but her research extends beyond the realm of statistics. Together with her group, her work has leveraged new computational developments to solve important scientific problems by combining novel statistical machine learning approaches with the domain expertise of her many collaborators in neuroscience, genomics and precision medicine.
She and her team develop relevant theory to understand random forests and deep learning for insight into and guidance for practice.

She is a member of the U.S. National Academy of Sciences and of the American Academy of Arts and Sciences. She is Past President of the Institute of Mathematical Statistics (IMS), Guggenheim Fellow, Tukey Memorial Lecturer of the Bernoulli Society, Rietz Lecturer of IMS, and a COPSS E. L. Scott prize winner. She holds an Honorary Doctorate from
The University of Lausanne (UNIL), Faculty of Business and Economics, in Switzerland.
She has recently served on the inaugural scientific advisory committee of the UK Turing Institute for Data Science and AI, and is serving on the editorial board of Proceedings of National Academy
of Sciences (PNAS).

Program Visits

Summer Cluster: Interpretable Machine Learning, Summer 2022, Visiting Scientist and Program Organizer
Summer Cluster: Deep Learning Theory, Summer 2022, Visiting Scientist and Program Organizer
Causality, Spring 2022, Visiting Scientist
Fields
veridical data science, interpretable machine learning, interdisciplinary research in genomics etc.