Evangelos Papoutsellis

Welcome to my website

I am Evangelos Papoutsellis (or Vaggelis) working at the intersection of applied mathematics, inverse problems, optimisation, tomography, machine learning, and open-source scientific software.

Research: My work focuses on imaging inverse problems, mathematical optimisation, and deep learning for building scalable algorithms that extract reliable information from complex, noisy, and high-dimensional data. I apply these methods to real-world applications in medical imaging, materials science, tomography, and chemical imaging.

Open-source software: I develop open-source research software that turns mathematical methods into practical, reproducible computational tools. This includes work on the Core Imaging Library (CIL), nDTomo, and the Synergistic Image Reconstruction Framework (SIRF), supporting optimisation, reconstruction, simulation, and analysis workflows for imaging and inverse problems.

Opportunities: I am currently open to new opportunities in computational imaging, scientific computing, applied mathematics, machine learning for imaging, and research software engineering, across academia, research institutes, and industry. I am especially interested in roles involving mathematical modelling, large-scale optimisation, algorithm development, tomographic reconstruction, and open-source scientific software.

For more details please see cv (updated May 2026).