Prof Fionn Murtagh

Staff details

Position Professor of Data Science (part-time)
Department Computing
Email f.murtagh (
Phone +44 (0)20 7919 7863
Prof Fionn Murtagh

Fionn has a strong track record in research with industrially-relevant consequences, and in teaching and learning. For over 35 years he has been a global leader in research, and applications, of clustering and data analysis, computational statistics, and also modelling and statistical analysis in image and signal processing.

He is editor-in-chief of Computer Journal, the British Computer Society’s flagship journal. He has a leading role in classification societies International Association for Statistical Computing and the British Computer Society, and has been president of both the Classification Society of North America and the British Classification Society. He is an elected member of the Royal Irish Academy and Academia Europaea.

Featured works

Short Courses and Tutorials

Summer School Course
Towards the New Science of Big Data Analytics, Based on the Geometry and the Topology of Complex, Hierarchic Systems
16-20 August 2015, ESSCaSS 2015, 14th Estonian Summer School on Computer and Systems Science, Nelijärve Puhkekeskus, Estonia.

The New Science of Big Data Analytics, Based on the Geometry and the Topology of Complex Systems
5 July 2015, at the Conference of the International Federation of Classification Societies, 6-8 July, 2015, Bologna, Italy.


  • SLDS, Symposium on Statistical Learning and Data Science, 20-22 April 2015, Royal Holloway, University of London. Programme Committee Co-Chair. Organiser, session on Geometric Data Analysis.

  • ISI2015, 60th World Statistics Congress, Organiser, Special Topic Paper Session (STS) on The New Data Science: Statistical Analysis of Massive, High Dimensional Systems, 26-31 July 2015, Rio de Janeiro, Brazil.

  • Statistical Computing for Data Science (Joint Meeting of IASC-ABE Satellite Conference for the 60th ISI WSC 2015 / IASC Satellite Conference 2015), 2-5 August 2015, Atlântico Búzios Convention and Resort, Búzios, RJ, Brazil. Member, Scientific Programme Committee.

  • ECDA, European Conference on Data Analysis, 2-4 September 2015, University of Essex.  Member Programme Committee.

  • p-Adics2015, International Conference on p-Adic Mathematical Physics and Its Applications, 7-12 September 2015, Belgrade, Serbia. Member Programme Committee, invited speaker.

  • CARME 2015, Correspondence Analysis and Related Methods, 20-23 September 2015, Naples, Italy.

  • Astroinformatics 2015, 5-9 October 2015, Dubrovnik, Croatia. Member Scientific Organising Committee.

  • CLA 2015, 12th International Conference on Concept Lattices and their Applications, 13-16 October 2015, Clermont-Ferrand, France. Invited Speaker. 

Research Interests

Data Science, Data Analytics, Big Data 

  • Digital Content Analytics
  • Computational Science, including innovative models and paradigms from digital humanities and quantitative social sciences
  • High Performance Search and Discovery, linear and constant computational time algorithms
  • Massive data sets in very high dimensional spaces
  • Geometry and topology of information and data
  • Narrativization
  • Multivariate Data Analysis Software
  • Multiscale Morphological Modelling, Compressive Sampling.



Starck, J-L.; Murtagh, Fionn and Fadili, J.. 2010. Sparse Image and Signal Processing: Wavelets and Related Geometric Multiscale Analysis. Cambridge University Press. ISBN 978-1107088061

Edited Book

Murtagh, Fionn; Hennig, Christian; Meila, Marina and Rocci, Roberto, eds. 2015. Handbook of Cluster Analysis. Chapman and Hall/CRC. ISBN 9781466551886

Book Section

Murtagh, Fionn and Contreras, Pedro. 2016. Linear Storage and Potentially Constant Time Hierarchical Clustering Using the Baire Metric and Random Spanning Paths. In: Adalbert F.X. Wilhelm and Hans A. Kestler, eds. Analysis of Large and Complex Data. Springer, pp. 43-52. ISBN ISBN-10: 3319252240 ISBN-13: 978-3319252247

Murtagh, Fionn and Contreras, P. 2016. Linear storage and potentially constant time hierarchical clustering using the Baire metric and random spanning paths. In: Adalberg F.X. Wilhelm and Hans A. Kestler, eds. Analysis of Large and Complex Data, Studies in Classification, Data Analysis, and Knowledge Organization. Springer, pp. 43-52. ISBN 978-3-319-25226-1

Murtagh, Fionn. 2015. Pattern recognition in mental processes: determining vestiges of the subconscious through ultrametric component analysis. In: S Patel; Y Wang; D Kinsner; G Patel; G Fariello and L.A. Zadeh, eds. Proc. ICCI*CC 2014, 2014 IEEE 13th Int'l. Conf. on Cognitive Informatics and Cognitive Computing. Springer, pp. 155-161.

Murtagh, Fionn. 2014. History of cluster analysis. In: Jörg Blasius and Michael Greenacre, eds. The Visualization and Verbalization of Data. CRC/Chapman and Hall, pp. 117-133. ISBN 978-1466589803

Murtagh, Fionn. 2014. Thinking ultrametrically, thinking p-adically. In: Fuad Aleskerov; Panos M. Pardalos and Boris Goldengorin, eds. Clusters, Orders, and Trees: Methods and Applications: In Honor of Boris Mirkin's 70th Birthday. Springer, pp. 249-272. ISBN 978-1493907410

Reddington, Joseph; Murtagh, Fionn and Cowie, Douglas. 2013. Computational Properties of Fiction Writing and Collaborative Work. In: Adam Tucker; F Hoppner; A Siebes and A Swift, eds. Advances in Intelligent Data Analysis XII, Lecture Notes in Computer Science Volume 8207. Springer, pp. 369-379. ISBN 978-3642413971


Murtagh, Fionn; Pianosi, Monica and Bull, Richard. 2016. Semantic mapping of discourse and activity, using Habermas’s theory of communicative action to analyze process. Quality and Quantity, 50(4), pp. 1675-1694. ISSN 0033-5177

Murtagh, Fionn and Kurtz, Michael J.. 2016. The Classification Society's Bibliography over four decades: History and content analysis. Journal of Classification, 33(1), pp. 6-29. ISSN 0176-4268

Murtagh, Fionn and Farid, M. 2015. The structure of argument: Semantic mapping of US Supreme Court cases. Lecture Notes in Computer Science, 9047, pp. 397-405. ISSN 0302-9743

Murtagh, Fionn and Contreras, P. 2015. Random projection towards the Baire metric for high dimensional clustering. Lecture Notes in Computer Science, 9047, pp. 424-431. ISSN 0302-9743

Murtagh, Fionn. 2014. Pattern recognition of subconscious underpinnings of cognition using ultrametric topological mapping of thinking and memory. International Journal of Cognitive Informatics and Natural Intelligence, 8(4), ISSN 1557-3958

Bosco, Filipe; Murtagh, Fionn; Emneus, Jenny; Agrell, Cecilia; Diamond, Dermot; Guiseppi-Elie, Anthony; Katusabe, Atkins; Lynch, Jim; Morse, Stephen; Moussy, Francis G; Nair, P.K.R; Weathers, Pamela J and Bell, Simon. 2014. Transdisciplinary Sustainability: The Council for Frontiers of Knowledge. International Journal of Transdisciplinary Research, 7(1), pp. 1-26.

Murtagh, Fionn. 2014. Mathematical Representations of Matte Blanco’s Bi-Logic, based on Metric Space and Ultrametric or Hierarchical Topology: Towards Practical Application. Language and Psychoanalysis, 3(2), pp. 40-63.

Murtagh, Fionn. 2014. "Ward's hierarchical agglomerative clustering method: Which algorithms implement Ward's criterion?". Journal of Classification, 31(3), pp. 274-295. ISSN 0176-4268

Murtagh, Fionn. 2013. 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, 5(4), pp. 326-337. ISSN 2070-0466

Conference or Workshop Item

Stamate, Daniel; Alghamdi, Wajdi; Stahl, Daniel; Pu, Ida; Murtagh, Fionn; Belgrave, Danielle; Murray, Robin and di Forti, Marta. 2018. 'Predicting First-Episode Psychosis Associated with Cannabis Use with Artificial Neural Networks and Deep Learning'. In: IPMU 2018: 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems. Cadiz, Spain.

Murtagh, Fionn; Olaniyan, Rapheal and Stamate, Daniel. 2015. 'A novel statistical and machine learning hybrid approach to predicting S&P500 using sentiment analysis'. In: 8th International Conference of the ERCIM Working Group on Computational and Methodological Statistics. Senate House, University of London, United Kingdom.