In November, the American Association for the Advancement of Science (AAAS) council elected nearly 500 members as fellows. A virtual induction ceremony for the 489 newly elected fellows will take place on February 13. The honorees will receive official certificates and rosette pins in gold and blue—colors symbolizing science and engineering—by mail.

The eight new fellows of AAAS Section U (Statistics) are listed below with their citations:

Sudipto Banerjee, University of California, Los Angeles
For innovative contributions to Bayesian methodology with focus on spatially indexed information; for high-impact applications; and for educational and mentoring excellence, professional service, and academic administration.

David L. Banks, Duke University
For leadership at the Statistical and Applied Mathematical Sciences Institute, research on risk analysis, and editorial service.

Deborah J. Donnell, Fred Hutchinson Cancer Research Center
For distinguished contributions to the field of HIV prevention research, particularly for design and analysis of clinical trials of pre-exposure prophylaxis and treatment as prevention.

Timothy C. Hesterberg, Google, Inc.
For excellent research in importance sampling and bootstrap methodology, important contributions to statistics education using resampling, and outstanding leadership and service to the profession.

Qi Long, University of Pennsylvania
For distinguished contributions to analysis of incomplete data, causal inference, and analysis of big data for advancing precision health.

Ying Lu, Stanford University School of Medicine
For distinguished contributions to the advancement of statistics in medical and biomedical research, particularly for the quality control and risk prediction associated with medical diagnosis.

Richard L. Smith, The University of North Carolina at Chapel Hill
For distinguished contributions to statistics, particularly the statistical analysis of extreme events and environmental applications, including climate change and air pollution.

Elizabeth A. Stuart, Johns Hopkins Bloomberg School of Public Health
For highly influential contributions to development and application of causal inference methods; for excellence in teaching and mentoring; and for distinguished professional leadership in statistics.