Prediction models constructed from state-space dynamics have a long and rich history, dating back to roulette and beyond. A major stumbling block in the application of these models in real-world ...

Dynamical systems theory underpins our modern understanding of complex behaviours that arise in both natural and engineered systems. At its core, this field addresses the evolution of systems over ...

Introduces the theory and applications of dynamical systems through solutions to differential equations.Covers existence and uniqueness theory, local stability properties, qualitative analysis, global ...

A new proof demonstrates the power of arithmetic dynamics, an emerging discipline that combines insights from number theory and dynamical systems. Joseph Silverman remembers when he began connecting ...

2025 marked a historic year in mathematics. Researchers solved a major case of Hilbert’s ambitious sixth problem, proved a sweeping new theorem about hyperbolic surfaces, and settled the longstanding ...

The course will survey methods for characterizing time-series data by reading primary literature and implementing and testing methods on synthetic data. Students will simulate time-series from a ...

Scientists usually use a hypergraph model to predict dynamic behaviors. But the opposite problem is interesting, too. What if researchers can observe the dynamics but don't have access to a reliable ...

The Nonlinear Systems and Control group is seeking a talented and ambitious Postdoctoral Researcher to develop machine learning-enabled approaches for predictive modelling and state estimation for ...