Conference: The 2026 Spring Research Conference of the ASA Section on Physical and Engineering Sciences: Harnessing Data for the Informative Advancement of Industry

The 2026 ASA Section on Physical and Engineering Sciences Spring Research Conference will be held in Clemson, South Carolina from May 26 – 28, 2026. The theme of the conference is Harnessing Data for the Informative Advancement of Industry. It aims to promote the development, communication, and implementation of state-of-the-art statistical and mathematical methodology toward the effective use of data in advancing industrial processes, materials science, engineering innovation, and manufacturing. The conference will bring together statisticians, data scientists, mathematicians, and domain experts to foster technical exchange, methodological advances, and engagement between academia, industry, and government. Particular highlights of the conference will include recent developments in uncertainty quantification, digital twins, computer experiments, reliability engineering, physics-informed machine learning, and challenges arising from smart manufacturing and advanced materials, including optimal design of experiments, Bayesian optimization, and multi-fidelity modeling. The conference will feature invited sessions, panels, and contributed presentations centered around engaging with emerging statistical challenges driven by complex data sources. The organizers seek to maximize participation from students, postdoctoral fellows, and early-career researchers. Conference details may be found online at https://sites.google.com/view/src2026 . This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2610968 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Derek Brown | Institution: Clemson University, CLEMSON, SC | Award Amount: $20,000 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2610968 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2610968.html