Theme: ‘Applications of Data Driven Fluid Dynamics’

University of Leeds

8th July-16th August 2024

We are pleased to announce the details of the NFFDy (National Fellowships in Fluid Dynamics) residential Summer Programme for 2024. The NFFDy scheme has been set up to support Early Career Researchers working in fluid dynamics on their pathway from PhD to PI.  The 11 NFFDy fellows are working for 3 years on a diverse range of research topics including superfluids, lava dynamics, self-cleaning surfaces and 4D flow-MRI, hosted and partnered by universities and other organisations across the UK.

The cohort of  NFFDy fellows benefit from participation in two residential Summer Programmes. The first of which was run by Cambridge in 2023. The programme in Leeds in 2024 will follow a similar structure, starting off with two weeks of lectures followed by four weeks of time to work on group projects, alongside sessions for group updates on progress, socials and professional development (e.g. careers support, EDI, policy, outreach). We will also support connections to industry partners/Leeds PhD students if you wish to include them on your project.

The focus of the programme will be on applications of data driven fluid dynamics and will include lectures on methodologies and examples of applications, including industry challenges and policy. Confirmed lecturers include

• Taraneh Sayadi (Sorbonne University, active learning for extracting generalisable ROMs of unsteady flows, data driven optimisation)
• Jean Christophe Loiseau (Ecole Nationale Supérieure d’Arts et Métiers, Sensors and actuators selection using submodular optimization for control problems, Large-scale bifurcation analysis using a non-intrusive time-stepper approach, General tour of the SINDy framework)
• Claire Heaney (Imperial College London, reduced-order modelling; machine-learning for scientific applications; urban and environmental flows)
• Calum Skene (University of Leeds, adjoint methods, dedalus 3 and optimisation)
• Matthew Juniper and Lloyd Fung (University of Cambridge, bayesian-SINDy).
• Hong Ge (University of Cambridge, probabilistic programming )
• Pedram Hassanzadeh (Rice University, methods and applications of AI)
• Simon Parker (DSTL, environmental sampling)

Updates to the programme will be posted here: Programme

Applications closed for full programme. It is still possible to attend the first two weeks of lectures only (open to PGRs and post-docs in the UK). £65pp. Please get in touch to request your place at [email protected]