Fionn Murtagh

Fionn Murtagh has worked in data analytics throughout his career. His first employment, following his primary degrees in Mathematics and Engineering Science, was as statistician-programmer in educational research, overseeing the regular national-level ability and attainment testing, as well as analytics research.

His MSc in Information Retrieval was followed by a PhD in Mathematical Statistics. After an initial period as lecturer in Computer Science, Fionn worked as a visiting researcher in nuclear reactor safety, at the European Joint Research Centre. He served with the Space Science Department of the European Space Agency for 12 years, on data analytics and databases, image and signal processing, and networking, for the Hubble Space Telescope.

He has published over 300 papers, approximately 150 in leading journals, and is author of eight books (with another four underway or to be published imminently).

Fionn Murtagh was a partner in a number of Framework Programme projects, KTPs, a COST Action, and projects funded by EPSRC, BBSRC and STFC (PPARC). Funded by the latter with approx. £9 million was Astrogrid, for datagrid middleware, for which Fionn was a Lead Investigator and a founder member.


Starck, J.-L., Murtagh, F. and Fadili, J., Sparse Image and Signal Processing: Wavelets, Curvelets, Morphological Diversity, Cambridge University Press, 2nd edn., 2015. (Chinese version in preparation.)
F. Murtagh, M. Pianosi, R. Bull, Semantic mapping of discourse and activity, using Habermas’s Theory of Communicative Action to analyze process, Quality and Quantity, 2015, in press.
P. Contreras and F. Murtagh, Fast, linear time hierarchical clustering using the Baire metric, Journal of Classification, 29, 118–143, 2012.
F. Murtagh, The new science of complex systems through ultrametric analysis: Application to search and discovery, to narrative and to thinking, Journal of p-Adic Numbers, Ultrametric Analysis and Applications, vol 5, no. 4, 326-337, 2013.
F. Murtagh, The remarkable simplicity of very high dimensional data: application to model-based clustering, Journal of Classification, 26, 249-277, 2009.
F. Murtagh and P. Contreras, Random projection towards the Baire metric for high dimensional clustering, A. Gammerman, V. Vovk and H. Papadopoulos, Eds, Statistical Learning and Data Sciences, Springer Lecture Notes in Artificial Intelligence (LNAI) Volume 9047, 424-431, 2015.