I. Sinclair, Multiscale and In Situ Laboratory X-Ray Computed Tomography National Research Facility

Staff

Professor of Engineering Materials

Connect with Ian

Email: I.Sinclair@soton.ac.uk

Head of Department

Research interests

My research focusses on computational tools, technologies and platforms and how they enable interdisciplinary problems to be solved in engineering and science.His team in the Computational Engineering and Design Group is applying and developing high performance and cloud computing in a variety of collaborative interdisciplinary computational science and engineering projects. These include:
High Performance and novel Computing SystemsCloud Computing and commercial distributed computing - which led to a spin out companyApplied computational algorithms Computational electromagnetics– which led to the formation of a spin-off company.New algorithms such as meshless methods and fast solvers.Data Management Simon is also Director of the Microsoft Institute for High Performance computing where he demonstrates why, where and how current and future Microsoft tools and technologies can be exploited to enable engineering and scientific research to deliver faster, cheaper and better results.

Connect with Simon

Email: S.J.Cox@soton.ac.uk

Professor

Research interests

I develop and study advanced algorithms that can solve challenging inverse problems by efficiently exploiting complex prior information. Using techniques from mathematics, statistics and machine learning, my work concentrates primarily on problems in x-ray tomographic image reconstruction and modelling.
I work closely with state-of-the-art imaging facilities (µ-VIS, the National Research Facility in Lab-based XCT, the UK’s synchrotron facility at the Diamond Light Source, and ISIS neutron imaging beamline) to find practical solutions to a range of important scientific problems from plant science to manufacturing.
My research interests cover areas such as: Theoretical and computational methods for Signal and Image Processing (Machine Learning, Compressed Sensing, Statistical Signal and Image Processing, Quantum Computing, Inverse Problems, Optimisation, X-ray Tomographic Imaging); Advanced tomographic imaging strategies: (limited angle tomography and laminography, Spectral X-ray imaging, Stereo and extreme limited view tomography); Efficient computational methods for tomographic reconstruction, including GPU acceleration, distributed computation and advanced optimisation strategies, Constrained optimisation for ill-conditioned and underdetermined tomographic inverse problems, Applications of X-ray tomography to the inspection of manufactured components, Multimodal tomographic imaging

Connect with Thomas

Email: Thomas.Blumensath@soton.ac.uk