The Frontiers of Statistics in Science and Engineering: Charting the Next Decade

The statistical sciences provide critical foundations for addressing today's most pressing scientific and technological challenges. As emerging technologies such as digital twins, wearable devices, and blockchain reshape research and industry, statistics ensures that discoveries are reliable, methods are validated, and decisions are grounded in evidence. Recognizing the need for a forward-looking perspective, the National Science Foundation, National Security Agency, and National Institutes of Health sponsored a National Academies of Sciences, Engineering, and Medicine consensus activity to conduct a decadal-like assessment of the discipline as it prepares for 2035 and beyond. The study committee's report presents a vision of statistics as an essential enabler of modern science and engineering. It highlights the vitality of recent research advances while identifying pressing methodological challenges raised by heterogeneous, high-velocity, and privacy-sensitive data. The report emphasizes the central role of statistics in shaping machine learning and artificial intelligence, showing how statistical principles underpin the scalability, fairness, and reliability of these technologies. It also identifies urgent needs for innovation in uncertainty quantification, capabilities that are indispensable for emerging tools such as large language models, digital twins, and hybrid systems that combine physics-based and data-driven components. Statistical expertise is equally critical in guiding policies on responsible data sharing, privacy protection, and the evaluation of complex models that are increasingly used to inform decisions in science, engineering, and society. Equally important, the study situates statistics as indispensable across the broader research and engineering ecosystem. From biomedical and health sciences to materials research, manufacturing, finance, energy, and environmental science, statistical methods are central to innovation and national competitiveness. By documenting these connections, the report makes clear that statistics is not a supporting actor but a foundational partner in advancing national priorities. It also underscores the importance of statistical innovation in enabling translational research, where new methods move rapidly from theory into applied domains with societal impact. The report further emphasizes education and workforce development, highlighting the need to prepare future statisticians and data-oriented scientists for interdisciplinary, data-rich environments. Training programs that combine methodological rigor with collaborative fluency and responsible practice will be essential for sustaining the discipline's impact. Committee members will present the study's major findings and recommendations, followed by a panel discussion including members of the study committee. The study may make recommendations to funding agencies on how to align and expand their portfolios to reflect the evolving discipline and strengthen its impact, thus ensuring that statistics continues to drive advances in science, engineering, and areas of national interest in the decade ahead. Committee Members: Katherine B. Ensor (Chair), Lance A. Waller (Vice Chair), Rina F. Barber, Amy Braverman, Lorin Crawford, David B. Dunson, Omar Ghattas, Frauke Kreuter, Xihong Lin, Brian Reich, Steve Sain, Aarti Singh, Daniela M. Witten, Tian Zheng.