Bin Yu

Bin Yu is a Chancellor’s Professor at the University of California, Berkeley, affiliated with the Departments of Statistics and Electrical Engineering & Computer Sciences. Her research focuses on statistics, machine learning theory, and methodologies for high-dimensional data analysis, with interdisciplinary applications in genomics, neuroscience, and remote sensing.

• PhD in Statistics, UC Berkeley (1990)
• MA in Statistics, UC Berkeley (1987)
• BS in Mathematics, Peking University (1984)

Her work includes pioneering the Predictability, Computability, and Stability (PCS) framework for veridical data science, emphasizing responsible AI development and reproducibility. Recent publications address transformer interpretability, domain adaptation, and medical AI ethics.

Scientific awards include:

• U.S. National Academy of Sciences Member (2014)
• American Academy of Arts and Sciences Member (2013)
• Guggenheim Fellow (2006)
• IMS Rietz Lecturer (2016)
• COPSS Elizabeth L. Scott Award (2018)

Research support includes collaboration with Eva Leach (eva.leach@berkeley.edu) and leadership roles at the Berkeley Artificial Intelligence Research Lab (BAIR) and the Microsoft Lab on Statistics and Information Technology in China.