The adoption of differentiable modeling and simulation has gained significant traction in computational science and engineering (CSE) workflows, driving advancements in optimization, sensitivity analysis, uncertainty quantification, model discovery, and more. This minisymposium brings together scientists, researchers, practitioners, students, and software developers who are either utilizing or developing differentiable computational models. We also welcome those seeking inspiration to integrate these methodologies into their own work. Our goal is to provide a platform for knowledge exchange and learning from each other's experiences—highlighting both success stories and challenges encountered along the way. We invite contributions that share experiences in developing differentiable computational models—including specific challenges faced, innovative solutions found—and applications of these models across various domains. Attendees can look forward to learning from notable contributors within the Julia community who will present innovative use cases while fostering collaboration among participants. Through networking opportunities and shared insights, we aim to inspire both seasoned users and newcomers by demonstrating how differentiable modelling can enhance model-based CSE workflows!
Alan Correa and Sarah Williamsom will host a minisymposium on "Differentiable Computational Models and their Applications" at JuliaCon 2026. Find out more at pretalx.com/juliacon-202... and submit your talk at juliacon.org/2026/cfp
#julialang #automaticdifferentiation
