The focus of this program is on identifying explicit dynamical structures in nonlinear systems that are high dimensional, poorly resolved, or both. In these problems, computational mathematics is often the only feasible way forward.

The first featured workshop explores the computational challenges of rigorously identifying and extracting fundamental dynamical features such as equilibria, periodic orbits, connecting orbits and invariant manifolds in infinite-dimensional dynamical systems. The second featured workshop investigates the development of computational algebraic topological tools for studying multiparameter, nonlinear systems where the nonlinearities are poorly defined.

The main aim is to identify, characterize, and predict nonlinear dynamics from high-dimensional time series data sets. Each workshop is preceded by a hands-on tutorial aimed at graduate students, postdocs and early- to mid-career mathematicians.

All activities are being held in room 5340 of the Pavillon André-Aisenstadt.