We are now accepting applications for an upcoming ICERM Workshop: Uncertainty Quantification for Mathematical Biology, taking place May 5-9, 2025. 

https://icerm.brown.edu/program/topical_workshop/tw-25-uqmb

Mathematical models play a vital role in understanding complex biological systems. However, these systems are often characterized by indirectly and partially observed, noisy, and high-dimensional dynamics and data. Current models often fail to adequately account for the various sources of uncertainty within the data, leading to inaccurate or incomplete models with limited explanatory power.

The field of uncertainty quantification (UQ) offers approaches to address these challenges. UQ is the mathematical study of how uncertainty influences and propagates through models, allowing researchers to quantify the impacts of uncertainty on model-based predictions, inference, and design. Despite its success in other scientific domains, the application of UQ techniques in mathematical biology remains underdeveloped.

This workshop capitalizes on the significant potential for mutual advancement in UQ and mathematical biology through cross-disciplinary collaboration. Bringing together UQ practitioners and mathematical biologists will allow UQ methodologies to be applied to explore and improve biological models through computational methods. Conversely, the unique challenges of modeling uncertainty in biological systems can inspire the development of novel UQ techniques. By fostering research collaborations at the intersection of computational and mathematical biology, UQ algorithms, and data-driven learning, this workshop aims to galvanize advancements across these fields.