Context: Over the past few decades computational modelling has continued to develop at a rapid pace as improvements in modern computer architectures have allowed computational scientists to tackle ever more challenging problems. However, real-life applications often consist of complex solution domains, multiscale features, and high-dimensional environments, which makes them computationally intractable unless novel numerical techniques, capable of reducing the model complexity, are employed.
Rigorous computational algorithms for partial differential equations (PDEs) are at the heart of these developments. In particular, adaptive algorithms exploited within finite element methods and model order reduction combined with machine learning techniques are now accepted among the key technologies for computational complexity reduction. Large parameter spaces demand for fast solvers and model reduction, with adaptive and learning approaches providing an essential tool for automatic numerical multiscale modelling.
Aim of the Research School: The aim of the school is to expose young researchers to state-of-the-art model reduction and adaptivity techniques for PDEs, showcasing their interplay and core position within computational modelling, machine learning and engineering applications. These topics are of vital importance to train the next generation of computational and data scientists.
- Andrea Cangiani, Scuola Internazionale Superiore di Studi Avanzati (SISSA)
- Paul Houston, University of Nottingham
- Kris van der Zee, University of Nottingham
Lecturers and Plenary Speakers (abstract and programme details to appear soon)
- Zhiqiang Cai, Purdue University
- Olga Mula, Université Paris-Dauphine
- Simona Perotto, Politecnico di Milano
- Serge Prudhomme, École Polytechnique de Montréal
- Gianluigi Rozza, Scuola Internazionale Superiore di Studi Avanzati (SISSA)
- Barbara Wohlmuth, Technische Universität München
- Andrea Cangiani - Paul Houston - Kris van der Zee
Registration details (further details to appear soon)
- The organisers anticipate that they will be able to cover full local expenses (accommodation and meals) for around 40 research students who have successfully secured a place.
- PhD student registration fee: £150 (tbc)
- Early Career Researcher (Postdoc) registration fee: £250 (tbc)
To register interest in this Research School, please click "here". The organisers will then keep you updated and let you know once you can apply for a place.
About LMS Research Schools
The London Mathematical Society Research Schools provide training for research students in all contemporary areas of mathematics. Students and post-docs can meet a number of leading experts in the topic as well as other young researchers working in related areas.
The LMS Research Schools take place in the UK and support participation of research students from both the UK and abroad. The lecturers are expected to be international leaders in their field. The LMS Research Schools are often partially funded by the Heilbronn Institute for Mathematical Research.