The 2026 Leo Breiman Award Committee of the ASA Statistical Learning and Data Science Section selected Tony Cai as the recipient of the Leo Breiman Senior Award and Yuxin Chen and Anru Zhang as recipients of the junior awards.
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.
Tony Cai—Senior Award
Tony Cai earned his PhD from Cornell University in 1996. He joined the University of Pennsylvania in 2006 and is currently the Daniel H. Silberberg Professor and professor of statistics and data science.
His research interests include high-dimensional inference, large-scale multiple testing, nonparametric function estimation, functional data analysis, and statistical decision theory—with applications in compressed sensing, medical imaging, and microarray data analysis.
Cai is recognized for deep theoretical insight and transformative methodological advances that have shaped both the foundations and practice of contemporary statistics and machine learning.
He received the Committee of Presidents of Statistical Societies Presidents’ Award in 2008, the Noether Distinguished Scholar Award from the American Statistical Association in 2023, and the Frontiers of Science Award at the 2023 International Congress of Basic Science. He was elected fellow of the Institute of Mathematical Statistics in 2006, president of the International Chinese Statistical Association in 2016, and fellow of the American Association for the Advancement of Science in 2024.
Yuxin Chen—Junior Award
Yuxin Chen is an associate professor of statistics and data science and of electrical and systems engineering at the University of Pennsylvania. Before joining UPenn, he was an assistant professor of electrical and computer engineering at Princeton University. He earned his PhD in electrical engineering at Stanford University and was a postdoc scholar at Stanford Statistics.
His research focuses on high-dimensional statistics, nonconvex optimization, and machine learning theory.
Chen is honored for outstanding research at the intersection of statistics, data science, and machine learning. His work has advanced the theoretical and algorithmic foundations of these fields while significantly expanding their frontiers.
His honors include the Alfred P. Sloan Research Fellowship, the SIAM Activity Group on Imaging Science Best Paper Prize, and the ICCM Best Paper Award (gold medal). He was also selected as a finalist for the Best Paper Prize for Young Researchers in Continuous Optimization. Additionally, he received the Princeton Graduate Mentoring Award.
Anru Zhang—Junior Award
Anru Zhang is a primary faculty member, jointly appointed in the department of biostatistics and bioinformatics and in the department of computer science at Duke University. He is also the Eugene Anson Stead Jr., MD, Associate Professor and serves as associate chair for research in the department of biostatistics and bioinformatics.
His research interests include generative models, biomedical data science, tensor learning, and high-dimensional statistics.
Zhang is recognized for outstanding method and theory research in machine learning and high-dimensional statistics and impactful applications for real-world challenges, particularly in the field of biomedical informatics. He has received the COPSS Emerging Leader Award, IMS Tweedie Award, ASA Gottfried E. Noether Junior Award, AMIA Data Science Outstanding Paper Award, and an NSF CAREER Award. Two of his PhD students have received the IMS Lawrence D. Brown Award. He currently serves as an associate editor for the Annals of Statistics, Journal of the American Statistical Association (Theory & Methods and Applications & Case Studies), Statistica Sinica, ASA Discoveries, and Statistics and Its Interface. His research is supported by two NIH R01 grants (one as sole PI and one as MPI with clinical investigators).
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