Papers & Reports
X. Li and N. Polydorides, ‘Time-efficient surrogate models of thermal modelling in laser powder bed fusion’, Additive Manufacturing, vol. 59, Part A,103122, 2022.
A. Upadhyay, M. Lengden, ... N. Polydorides et al. ‘Tomographic imaging of carbon dioxide in the exhaust plume of large commercial aero-engines’, Applied Optics, 61(28), 2022.
R. Kruse, N. Polydorides and Y. Wu, ‘Application of randomized quadrature formulas to the finite element method for elliptic equations’, ArXiv preprint, 2021.
D. Kamilis, M. Blatter and N. Polydorides, ‘Learned spectral computed tomography’, ArXiv preprint, 2021.
X. Li and N. Polydorides, ‘A reduced Gaussian process heat emulator for laser powder bed fusion’, 8th Changeable, Agile, Reconfigurable, and Virtual Production Conference (CARV2021).
R. Lung, Y. Wu, D. Kamilis and N. Polydorides, ‘A sketched finite element method for elliptic equations’, Computer Meth. in Appl. Mech. & Eng., vol. 134, 2020.
Y. Wu and N. Polydorides, ‘A multilevel Monte Carlo estimator for matrix multiplication', SIAM J. Sci. Comput., 42(5), A2731–A2749, 2020.
D. Kamilis, N. Polydorides, S. Lee and J. Desjardins, ‘Spectral X-ray CT for fast NDT using discrete tomography', Proceedings of the Solid Freeform Foundation Symposium, 2019.
D. Kamilis and N. Polydorides, ‘Uncertainty quantification for low-frequency, time-harmonic Maxwell equations with stochastic conductivity models’, SIAM/ASA Journal of Uncertainty Quantification, 6(4), 1295-1334.
N. Polydorides, ‘Electrode modelling and image reconstruction in Lorentz force impedance tomography’, Physiological Measurement, 39(4), IoP, 2018. [link]
N. Polydorides, A. Tsekenis, E. Fisher, A. Chighine, H. McCann, L. Dimiccoli, P. Wright, M. Lengden, T. Benoy, D. Wilson, G. Humphries and W. Johnstone, ‘Constrained models for optical absorption tomography’, Applied Optics, 57(7), B1-B9, 2018. [link]
S. Tsekenis and N. Polydorides, ‘Optical access schemes for high speed and spatial resolution optical absorption tomography in energy engineering’, IEEE Sensors Journal, 17(24), 2017. [link]
Y. Bao, J. Jia and N. Polydorides, ‘Real-time temperature field measurement based on acoustic tomography, Measurement Science and Technology’, 28(7), 2017.
N. Polydorides, H. McCann, S. A. Tsekenis, V. Prat Archila and P. Wright, ‘An effcient approach for limited-data chemical species tomography and its error bounds’, Proceedings A of The Royal Society, 472: 20150875, 2016.
A. Baltopoulos, N. Polydorides, L. Pambaguian, A. Vavouliotis and V. Kostopoulos, ‘Exploiting carbon nanotube networks for damage assessment of fibre reinforced composites’, Composites Part B: Engineering, 76, 149-158, 2015.
N. Polydorides and F. Delbary ‘Marine Electrical Sensing for Detecting Small Inhomogeneities’, IEEE Trans. in Geoscience and Remote Sensing, 53(2), 988-1000, 2015.
A. Baltopoulos, N. Polydorides, L. Pambaguian, A. Vavouliotis and V. Kostopoulos, ‘Damage identification in carbon fiber reinforced polymer plates using electrical resistance tomography mapping’, SAGE Journal of Composite Materials, 47(26), 3285-3301, 2013.
N. Polydorides, M. Wang and D. Bertsekas, ‘A Quasi Monte Carlo method for large-scale inverse problems’ in Monte Carlo and Quasi-Monte Carlo Methods 2010, (ed.) H. Wozniakowski and L. Plaskota, Springer, 2012.
N. Polydorides, A. Aghasi and E. L. Miller, ‘High-order regularized regression in Electrical Impedance Tomography’, SIAM J. Imaging Sciences, 5(3), 912-942, 2012.
N. Polydorides and E. Storteig, ‘Ocean current inference using towed cable hydrodynamics’, ASCE Journal of Waterway, Port, Coastal, and Ocean Engineering, 138(2), 2-8, 2012.
N. Polydorides, ‘A stochastic simulation method for uncertainty quantification in the linearized inverse conductivity problem’, International Journal for Numerical Methods in Engineering, 90(1), 22-39, 2011.
N. Polydorides, ‘The linearization error in electrical impedance tomography’, Progress in Electromagnetic Research, 93, 323-337, 2009.
N. Polydorides, E. Storteig and W.R.B. Lionheart, ‘Ocean current estimation in towed cable hydrodynamics under dynamic steering’, Inverse Problems in Science and Engineering, 17(5), 627-645, 2009.
N. Polydorides, E. Storteig and W.R.B. Lionheart, ‘Forward and inverse problems in towed cable hydrodynamics’, Ocean Engineering, Elsevier Science, 35(14-15), 1429-1438, 2008.
N. Polydorides, D-H Kim, C. Won and G.E. Georghiou, ‘Subspace constrained regularization for corrosion detection with magnetic induction tomography’, NDT&E International, 41(7), 510-516, 2008.
A. Kyprianou, N. Loucaides, N. Polydorides, G. E. Georghiou, C. Charalambous, C. Doumanides , ‘Stochastic control for nanoparticle manipulation using electric fields’, International Journal of Nanomanufacturing, 1(6), 751-761, 2007.
N. Polydorides, A. Kyprianou and C.D. Charalambous, ‘Numerical modeling for atomic force microscopy based impedance imaging’, Part N, Journal of Nano-engineering and Nanosystems, 219(4), pp. 147-156, 2006.
M. Soleimani, C. Powell and N. Polydorides, ‘Improving the forward solver for the complete electrode model in EIT using algebraic multigrid’, IEEE Transactions on Medical Imaging, 24(5), 577-583, 2005.
N. Polydorides and H. McCann, ‘Electrode configurations for improved sensitivity in Electrical Impedance Tomography’, Measurement Science and Technology, 13(12), 1862-1870, 2002.
N. Polydorides, ‘High contrast electrical impedance imaging’, Proceedings in Industrial Mathematics at ECMI, Springer, 2008.
W.R.B. Lionheart, N. Polydorides and A. Borsic, ‘The image reconstruction problem’, in (ed) D.S. Holder ‘Electrical Impedance Tomography: Methods, History and Applications’, ISBN:0750309520, IOP Publishing, Bristol, UK, 2004.
N. Polydorides and W.R.B. Lionheart, ‘A MATLAB based toolkit for three-dimensional Electrical Impedance Tomography: A contribution to the EIDORS project’, Measurement Science and Technology, 13(12), 1871-1883, 2002.
N. Polydorides, W.R.B. Lionheart and H. McCann, ‘Krylov subspace iterative techniques: On the detection of brain activity with Electrical Impedance Tomography’, IEEE Transactions on Medical Imaging, 21(6), 596-603, 2002.
PhD Theses
D. Kamilis, ‘Uncertainty Quantification for low-frequency Maxwell equations with stochastic conductivity models’, University of Edinburgh, 2018 [pdf]