Computational Sciences and Engineering

Our expertise 

We combine mathematics, physics, computer science, and engineering to create digital representations of real-world systems. By developing advanced models and simulation tools, we enable faster innovation, reduced risk, and better decision-making in areas such as energy, maritime operations, manufacturing, mobility, and environmental technology. 

Our research spans the entire modelling and simulation pipeline – from mathematical theory and numerical methods to scalable software and industrial applications. We work with high-fidelity simulations, reduced-order models, digital twins, and AI-enhanced computational methods that make complex analyses faster and more accessible. 

How do we work? 

We combine deep expertise in applied mathematics, scientific computing, and engineering with a strong understanding of industrial challenges. Our researchers develop new algorithms and computational methods while ensuring that they can be deployed in practical, real-world settings. 

A key part of our work is bridging the gap between advanced numerical simulations and operational decision support. We integrate physics-based models, data-driven approaches, and high-performance computing to create reliable tools for design, optimisation, monitoring, and prediction. 

Our research includes: 

• Numerical modelling using finite element, finite volume, and isogeometric methods 
• Computational fluid dynamics and solid mechanics 
• Multiphysics and coupled systems 
• High-performance computing and scalable algorithms 
• Reduced-order modelling and real-time simulation 
• Digital twins and virtual testing environments 
• AI and machine learning for physics-based modelling 
• Open-source scientific software and research infrastructure 

What sets us apart? 

Our strength lies in combining world-class expertise in computational mathematics and scientific computing with decades of experience solving industrial problems. 

We develop methods that are both scientifically rigorous and practically relevant. By integrating mathematical modelling, simulation, AI, and digital twin technologies, we create solutions that enable organisations to test, analyse, and optimise systems digitally before acting in the real world. 

The group has a strong track record of developing widely used software, contributing to international research collaborations, and transferring advanced computational methods into operational use across multiple sectors. 

International orientation 

Computational challenges are global, and so is our research. We collaborate closely with leading universities, research institutes, and industrial partners across Europe and beyond. 

Our researchers participate in international projects and scientific networks spanning computational science, digital twins, scientific machine learning, high-performance computing, and engineering simulation. Through these collaborations, we contribute to advancing the state of the art while ensuring that new knowledge creates value for industry and society. 

Selected research topics 

• Digital twins and virtual environments 
  We develop digital twins that combine simulation models, sensor data, and AI to provide continuous insight into the behaviour and condition of physical systems. These technologies support monitoring, optimisation, predictive maintenance, and decision-making throughout a system's lifecycle. 
• Scientific machine learning 
  By combining physics-based models with artificial intelligence, we create computational methods that are faster, more robust, and capable of extracting value from both data and domain knowledge. 
• Simulation-driven engineering 
  We develop advanced simulation methods for fluid flow, structural mechanics, and coupled physical processes. These methods enable virtual testing and design optimisation, reducing costs, development time, and environmental impact. 
• High-performance computing 
  Many of today's engineering and scientific challenges require massive computational resources. We develop scalable algorithms and software that take advantage of modern computing architectures to solve increasingly complex problems efficiently.