ASA members Mark van der Laan and Weili He have been honored with lecture awards from the International Society for Biopharmaceutical Statistics.
Cai, Chen, and Zhang Honored with Breiman Award
The awards recognize senior and junior scholars for outstanding theoretical or methodological contributions in machine learning and/or computational statistics. These contributions have made substantial and sustained effects on the practical application and study of these fields.
ASA Members Elected AAAS Fellows
Election as a AAAS Fellow honors those whose advancement of science and service to society have distinguished them among their peers and colleagues.
NYC Chapter Hosts Treasure Hunt Through Open Data
Members of the ASA’s New York City Chapter learned hands-on statistical problem solving during Open Data Week.
QPRC to Focus on Advancing Industrial Statistics for Complex Systems
Registration is open for the 2026 Quality and Productivity Research Conference, which brings together researchers and practitioners in Santa Fe, New Mexico.
SRMS Looks Forward to Roundtable, Invited Paper Sessions at JSM
The Survey Research Methods Section is sponsoring the roundtable “Realistic Business Models for Production and Dissemination of High-Quality Statistical Information.”
Growing on Purpose
ASA President Jeri Mulrow explores how members can take advantage of opportunities to build skills, expand networks, and grow with purpose.
Celebrating Women in Statistics and Data Science
In honor of Women’s History Month, we’re celebrating remarkable women in statistics, biostatistics, and data science. As mentors, educators, and influencers, they’ve shaped the field in countless ways. Read their journeys and learn about their incredible achievements.
Donna Brogan
Denied technical roles early in her career, Donna Brogan went on to earn a PhD and became a pioneer in biostatistics and women’s health. As a founder of the Caucus for Women in Statistics and Data Science, her legacy reaches far beyond her research.
Grace Wahba
While working full time and raising a child, Grace Wahba earned advanced degrees, completing her PhD at Stanford. She pioneered smoothing splines, shaping modern nonparametric regression and leaving a lasting imprint on data analysis and machine learning.