Global statistics body ISI welcomes new cohort of distinguished members in 2026

The International Statistical Institute (ISI), one of the world’s oldest and most respected organizations in the field of statistics, has announced its first cohort of newly elected members for 2026. The diverse group of 20 statisticians and data scientists’ hails from nine countries across five continents, reinforcing the Institute’s commitment to recognizing excellence on a truly global scale.

Established in 1885 and headquartered in The Hague, Netherlands, the ISI operates as a non-profit, non-governmental body with members in over 150 countries. It has held consultative status with the United Nations Economic and Social Council since 1947 and serves as the central global network connecting statisticians and data scientists from government, academia, and the private sector. The organization encompasses seven specialized associations and hosts the prestigious biennial World Statistics Congress.

ISI Elected Membership is a prestigious distinction reserved for individuals who have consistently demonstrated exceptional achievements and significant contributions in the field of statistics. The selection process is overseen by the ISI Membership Elections Committee, which conducts four election rounds annually. In 2025, approximately 40 professionals were elevated to this status.

Few distinguished statisticians from Arizona also hold this globally recognized professional status, including Sally C. Morton of Arizona State University, who serves as Executive Vice President of Arizona State University and is a former president of the American Statistical Association, with deep contributions in health and policy analytics. From the University of Arizona, Hao Helen Zhang is a leading scholar in statistical learning and data mining, known for her work in modern machine learning methods and holds Fellow of Institute of Mathematical Statistics and American Statistical Association. Another prominent figure, Sharon Lohr, an emeritus Dean’s distinguished professor at Arizona State University, who holds Fellow of American Statistical Association, is widely respected for her contributions to survey sampling and applied social statistics.

The 2026 first-round electees include Karol Patryk Binkowski, Paul Pao-Yen Wu, Fábio Mariano Bayer, Dharmateja Priyadarshi Uddandarao, Rob Deardon, Nathaniel Kenneth Newlands, Hao Mei, Yumou Qiu, Mengxin Yu, Peter Johnson Mannepalli, Praveen Gupta Sanka, VS Vaidyanathan, Pei-Fang Su, Sounak Chakroborty, Paola Crippa, Sujit Kumar Ghosh, Monnie McGee, Wanli Qiao, Lihu Xu, Panpan Zhang, and Xin Zou.

Profiles of Notable Electees

Fábio Mariano Bayer serves as Associate Professor at the Federal University of Santa Maria and researcher with the Santa Maria Space Science Laboratory in Brazil. His work spans digital signal processing, statistical computing, and regression models, with more than 100 peer-reviewed articles published in high-impact international journals.

Paola Crippa, an Assistant Professor at the University of Notre Dame with a joint appointment in Statistics and Civil and Environmental Engineering, is a recipient of the 2023 NSF CAREER Award and the 2015 L’Oréal-UNESCO Fellowship for Women in Science. Her research advances environmental statistics through Bayesian, non-Gaussian, and machine-learning methods.

Dharmateja Priyadarshi Uddandarao is an expert statistician currently working at Amazon, making him one of the few industry professionals to receive this honor. He holds a rare trifecta of professional accreditations, AdvDSP from the Alliance for Data Science Professionals, PStat from the American Statistical Association, and CStat from the Royal Statistical Society. His contributions include numerous articles and books on novel causal inference methods, particularly pre-balanced causal techniques that advances observational study designs.

Mengxin Yu, an Assistant Professor at Washington University in St. Louis, specializes in uncertainty quantification, causal inference, and robust high-dimensional statistics. Her interdisciplinary collaborations with clinicians have yielded data-driven advances in cerebral malaria, digital health, and Alzheimer’s disease research.

Rob Deardon is a Professor of Biostatistics at the University of Calgary with a joint appointment in the Faculty of Veterinary Medicine and the Department of Mathematics & Statistics. Currently serving as President of the Statistical Society of Canada, his research focuses on infectious disease modelling, spatial epidemiology, and Bayesian statistical methods.

Monnie McGee, Associate Professor at Southern Methodist University, develops statistical methods for complex, high-dimensional data with applications in biomedicine, sports analytics, and artificial intelligence. She currently chairs the ASA Committee on Publications and serves on a National Academies panel on the future of statistics.

Nathaniel Kenneth Newlands is a Senior Research Scientist and Team Lead of Data Science within Agriculture and Agri-Food Canada, and Adjunct Professor at the University of Victoria. He currently serves as President of the International Environmetrics Society (TIES) and Editor-in-Chief of the journal Applied Statistics: Environmental Statistics and Data Science.

Praveen Gupta Sanka is a seasoned data scientist with over a decade of experience in analytics. He has authored articles on artificial intelligence, agentic AI platforms, and machine learning, bridging advanced analytical methods with practical business applications. He is actively engaged in the broader data science community through mentoring, peer reviewing, and leadership roles in organizations such as IEEE and the ASA.

Paola Crippa, an Assistant Professor at the University of Notre Dame with a joint appointment in Statistics and Civil and Environmental Engineering, is a recipient of the 2023 NSF CAREER Award and the 2015 L’Oréal-UNESCO Fellowship for Women in Science. Her research advances environmental statistics through Bayesian, non-Gaussian, and machine-learning methods.

Panpan Zhang is an Assistant Professor of Biostatistics at Vanderbilt University Medical Center and co-leader of the Data Management and Statistics Core of the Vanderbilt Alzheimer’s Disease Research Center. His methodological contributions span longitudinal data analysis, causal inference, and network-based modelling for neuroimaging and cognitive markers.

Karol Patryk Binkowski is a statistician and academic at Macquarie University in Sydney, specializing in quantitative risk analysis. His research includes stochastic modelling, commodity pricing, and statistical methods for financial applications, bringing a distinctive blend of industry experience and academic rigor to the profession.

The ISI’s continued recognition of professionals across diverse specializations underscores the expanding role of statistical science in addressing complex global challenges. With its nearly 140-year legacy, the Institute remains at the forefront of fostering international collaboration and advancing best practices in statistics and data science worldwide.