Data Driven Prediction in Dynamical Systems

About the Project

The need to comprehend and predict the dynamics of complex systems have spurred developments in large-scale simulations and a multitude of methods across several disciplines. The goals of understanding and prediction in complex dynamical systems, however, have been hindered by high dimensionality, complexity and chaotic behaviours. Recent advances in data-driven techniques and machine-learning approaches have revolutionized how we model and analyse complex systems. The integration of these techniques with dynamical systems theory opens up opportunities to tackle previously unattainable challenges in modelling and prediction of dynamical systems. In this project we will explore various complex systems using model free prediction techniques such as reservoir computing. Reservoir computing (RC) is a computation framework that uses a Recurrent Neural Network but does not update all the parameters of the network.

Department and Campus

Department of Mathematics, School of Physical Sciences, Coimbatore

Skillsets Preferred from Applicants

Good computational skill is essential.