Integrating Data- and Physics-Driven Methods for Decision Making under Uncertainty (26w5632)

The Casa Matemática Oaxaca (CMO) will host the "Integrating Data- and Physics-Driven Methods for Decision Making under Uncertainty" workshop in Oaxaca, from May 31 to June 5, 2026.

In an era marked by significant advances across science, technology, engineering, and mathematics, a critical frontier lies in addressing the intricate challenges posed by uncertainties in computational science. The upcoming workshop on "Integrating Data- and Physics-Driven Methods for Decision Making under Uncertainty" is set to convene leading experts, researchers, and practitioners at the forefront of data-enabled science and data-intensive, large-scale inverse problems. The workshop aims to explore innovative methodologies, data- and compute-scalable algorithms, and real-world applications to bridge the gap between models and data, ultimately paving the way for informed real-time decision-making in critical domains such as human and animal health, manufacturing, and climate prediction.

From intricate parameter-to-observation maps in complex dynamical systems to high-dimensional unknowns, the challenges encompass multi-scale and coupled multiphysics behaviors. With a surge in data availability, the imperative for algorithms seamlessly integrating model-based and data-driven frameworks becomes paramount. This workshop presents a unique opportunity for researchers to showcase advancements in theory, computation, and scalability, bringing together the realms of mathematics, computational sciences, and engineering to tackle real-world challenges head-on. By fostering interdisciplinary collaboration and promoting concrete outcomes, the workshop seeks to catalyze mathematical innovation.

With a focus on uncertainty characterization and propagation to decision-making,
we aim to lay the groundwork for transformative advancements for real-world problems.

This platform will not only drive collaboration among experts but also empower early and mid-career scientists to present their cutting-edge research and network with their peers. This sets the stage for collaborative solutions at the intersection of machine learning, statistical inference, and dynamical systems with applications to key technologies such as digital twins.

The Casa Matemática Oaxaca (CMO) in Mexico, and the Banff International Research Station for Mathematical Innovation and Discovery (BIRS) in Banff, are collaborative Canada-US-Mexico ventures that provide an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. The research station in Banff is supported by Canada's Natural Science and Engineering Research Council (NSERC), the U.S. National Science Foundation (NSF) and Alberta Technology and Innovation. The research station in Oaxaca is funded by UNAM and IIMAS.