Thomas Blumensath is a Professor of Signal and Image Processing at the University of Southampton and a Fellow at the Alan Turing Institute.
Thomas is the Director of Research at the Institute of Sound and Vibration Research and a member of the Signal Processing, Audio and Hearing research group (SPAH) and a member of the Institute for Life Sciences.
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- 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
My current research interests include efficient tomographic reconstruction, machine learning methods for tomographic imaging, spectral x-ray tomography, mulitmodal imaging, anomaly detection and related topics.
My research interests cover a range of areas, including:
- Theoretical and computational methods for Signal and Image Processing, including:
- Machine Learning
- Compressed Sensing
- Statistical Signal and Image Processing
- Quantum Computing
- Inverse Problems
- X-ray Tomographic Imaging
- Advanced tomographic imaging strategies, such as 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
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I teach topics from fundamental Engineering Mathematics and Programming to advanced Machine Learning, Robotics and Signal and Image processing.
- I am programme lead for the BEng Control Engineering programme at our Joint Education Institute with Harbin Engineering University
- I teach the Introduction to Machine Learning module (FEEG6042)
- I teach Biomedical Image Processing as part of our Biomedical Applications of Signal and Image Processing module (ISVR6138)
- I teach Arduino microcontroller programming for our engineering undergraduate programme (FEEG2001)
- I teach Computer Vision on our Robotic Systems module (JEIG3004)
- I supervise undergraduate and taught postgraduate research projects (FEEG3003. FEEG6012)
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Thomas received a B.Sc. (Hons) in Music Technology and Audio System Design from the University in Derby in 2002 and, in 2006, a PhD in Electronic Engineering (Bayesian Signal Processing) from the University of London. Since 2005, he held various appointments as Postdoctoral Researcher and Research Fellow working at the Centre for Digital Music at Queen Mary University of London, the Institute for Digital Communications at the University of Edinburgh, the Applied Mathematics Research Group at the University of Southampton and the University of Oxford's Centre for functional MRI of the brain.
In 2012 he joined the Institute of Sound and Vibration Research, where he worked as a New Frontiers Fellow, a Lecturer (since 2015) an Associate Professor (since 2017) and a Professor (since 2022). As an engineer and mathematician, his work spans theoretical and applied aspects of Signal and Image processing, concentrating particularly on Industrial applications of computed tomography and related volumetric imaging problems.
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