Joanna Slawinska: Data-driven spectral analysis and nonparameteric predictions of climate dynamics

Bio

Joanna has a comprehensive multidisciplinary background, including a Masters degree in Physics with a focus on theoretical astrophysics and stellar pulsations, a PhD in Computational Fluid Dynamics for geophysical flows, and postdoctoral research training in Applied Mathematics. Joanna is a Research Associate working on a range of topics, from theoretical development of data-driven methods for dynamical systems, to their subsequent application in physics and engineering. In particular, the current focus of her work is on machine learning techniques for analysis of spatiotemporal patterns of climate dynamics, and novel objective frameworks for AI forecasting of complex systems, including risks of relevance to industry and society.