Nicholas Polydorides

Professor Nicholas Polydorides holds the Personal Chair in Computational Engineering at the University of Edinburgh's School of Engineering. He leads the Agile Tomography Group specializing in inverse problems for electromagnetic and chemical species tomography with applications in biomedical imaging, geophysics, and industrial processes.

Education:

• PhD in Electrical Tomography, University of Manchester (2002)
• MSc in Computation, University of Oxford (1999)
• BEng in Electrical Engineering and Electronics, UMIST (1998)

Research focuses on the intersection of mathematical modeling, signal processing, and optimization for solving inverse problems in tomography. Key applications include low-frequency electromagnetic imaging, chemical species tomography for aerospace engines, and medical imaging techniques. Current projects involve laser-based combustion species monitoring and real-time process diagnostics for manufacturing.

Recent publications demonstrate advancements in spectroscopic sensing for turbine exhaust monitoring, Wi-Fi based health sensing, and computational methods for additive manufacturing. His group develops algorithms for large-scale electromagnetic field modeling and image reconstruction.

As Head of the Institute for Digital Communications (IDCOM), he oversees research in signal processing and imaging. He is an Alan Turing Institute Fellow and serves on EPSRC's strategic advisory teams for ICT and Mathematical Sciences.