About us
Our research explores nonlinear dynamics and data science applied to fluid problems. We combine concepts from dynamical systems with machine learning to better understand and control turbulence. Our work spans both conventional (Newtonian) and complex fluids, which present fascinating and unexpected phenomena, like chaos in the absence of inertia. We investigate these complex dynamics through large-scale numerical simulations alongside low-order modeling and analytical approaches. Additional research interests include the stability of complex fluid jets and selected aspects of biological flows.
Are you interested in our work and want to discuss about it or join us? Don’t hesitate to get in touch!
Main interests
The Navier-Stokes equations and their variations (nonlinear dynamics, transition, and turbulence)
Machine Learning and optimisation (deep reinforcement learning, model reduction, and topology optimisation)
“Squishy” systems, such as viscoelastic flows (elastic and elasto-inertial turbulence)