The winners of the inaugural David Cox Medal for Statistics have been revealed, recognizing three outstanding mid-career statisticians whose contributions have significantly advanced the field.
The first-ever recipients of this prestigious international prize are:
- Professor Eric Tchetgen Tchetgen (University of Pennsylvania), for his contributions to causal inference, including Proximal Causal Inference and instrumental variable methodology.
- Professor Nancy Zhang (University of Pennsylvania), for her work in statistical genomics, which has deepened our understanding of cancer genome evolution and biomedical research applications.
- Professor Richard Samworth (University of Cambridge), for his contributions to methodological and theoretical statistics, particularly in shape-constrained modeling and change-point analysis.
This newly established award, introduced in 2025, honors the legacy of Sir David Cox, a pioneering statistician and former president of the Royal Statistical Society. It celebrates researchers whose work in statistical theory, methodology, and applications has demonstrated originality, depth, and meaningful impact.
Professor Peter McCullagh, Chair of the Prize Committee, remarked:
"Sir David Cox’s work had a profound influence on statistics, making this recognition particularly meaningful. The contributions of Eric, Nancy, and Richard exemplify the same spirit of innovation and excellence that he embodied. We are delighted to celebrate their remarkable achievements."
The David Cox Medal for Statistics is jointly awarded by six leading statistical organizations: the Royal Statistical Society, American Statistical Association, Bernoulli Society, International Biometric Society, Institute of Mathematical Statistics, and the International Statistical Institute.
Full Citations for the Recipients:
Richard Samworth – Statistical Theory
Richard Samworth, FRS is awarded the David Cox Medal for Statistics for his outstanding contributions to methodological and theoretical statistics. Richard has made numerous seminal contributions including to shape-constrained modelling, high-dimensional statistics, change-point analysis, and nonparametric classification. These important and broad areas of statistical science encompass the majority of the prevailing topics where statistics has focused over the past two decades, and Richard has been at the forefront from the outset. In addition to his stellar research contributions, Richard has mentored with distinction many students and young researchers, as well as serving the profession tirelessly through journal editorships and other contributions to multiple statistical societies.
Tchetgen Tchetgen – Statistical Methodology
Eric Tchetgen Tchetgen is awarded the David Cox Medal for Statistics for his outstanding contributions to the development of pioneering statistical theory and methods that have reshaped our understanding and practice of causal inference. Eric’s noteworthy contributions recognized by this award include the development of Proximal Causal Inference and groundbreaking contributions to instrumental variable methodology, two fundamental analytic frameworks for credible causal inference in the face of intractable confounding. Beyond his groundbreaking works on proximal inference and instrumental variables, Eric has made seminal contributions to multiple other areas, including interference, mediation analysis, missing data, conformal inference, survival analysis, higher-order influence functions, and data fusion.
Nancy Zhang – Statistical Application
Nancy Ruonan Zhang is awarded the David Cox Medal for Statistics for her pioneering contributions to statistical genomics, particularly in cancer and single-cell genomics and their applications in biomedical research. Her work has advanced the analysis of high-dimensional biological data through the development of methods for change-point detection and false positive control, noise reduction in single-cell RNA sequencing, single-cell and spatial omic data integration, and cell type deconvolution in bulk tissue analysis. She has also made significant contributions to understanding cancer genome evolution through the development of allele-specific DNA copy number estimation methods that reveal intratumor heterogeneity. Through these contributions, Nancy has demonstrated exceptional leadership in bridging statistical innovation with real-world biomedical challenges, significantly influencing both the statistical and life sciences communities.
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