Some of our Recent Refereed Papers
 Restocchi V., Gaete Villegas J. and Fleuriot J. D. (2022). Multimorbidity profiles and stochastic block modeling improve ICU patient clustering. Artificial Intelligence for Health 2022. To appear in the proceedings of IEEE/ACM CCGRID 2022.
 Schmoetten R., Palmer J., and Fleuriot J. D. (2021). Formalising Geometric Axioms for Minkowski Spacetime and WithoutLossofGenerality Theorems. Proceedings of the 13th International Conference in Automated Deduction in Geometry, Electronic Proceedings in Theoretical Compuster Science (EPTCS) 352, 116128.
 Burton J, McMinn M., Vaughan J., Fleuriot J., Guthrie B. (2021). Carehome outbreaks of COVID19 in Scotland March to May 2020: national linked data cohort analysis. Age and Ageing Journal, Volume 50, Issue 5, September 2021, 1482–1492, Oxford University Press.
 Papapanagiotou P. and Fleuriot J. (2021). Objectlevel Reasoning with Logics Encoded in HOL Light. Electronic Proceedings in Theoretical Computer Science 332, pp. 18–34.
 Fleuriot J. D. (2021). Mechanizing Mathematics: From Dream to Reality. Chapter to appear in Mathematical Reasoning: The History and Impact of the DReaM Group (Ed. G. Michaelson), Springer
 Papapanagiotou P., Vaughan J., Smola F, and Fleuriot J. (2020). A Realworld Case Study of Process and Data Driven Predictive Analytics for Manufacturing Workflows. Proceedings of the 54th Hawaii International Conference on System Sciences (HICSS54).
 Wingfield L., Ceresa C., Thorogood S., Fleuriot J, Knight S. (2020). Artificial Intelligence and Liver Transplant: Predicting Survival of Individual Grafts, A Systematic Review. In American Association for the Study of Liver Diseases, Liver Transplantation, Wiley.
 Wingfield L., Ceresa C., Fleuriot J, Knight S. (2019). Artificial Intelligence for Liver Transplant (AI4T): Predicting Graft Survival. ASiT/TMS Poster of Distinction Prize. Association of Surgeons in Training International Surgical Conference 2019, British Journal of Surgery (BJS), Volume 106, Issue S6.
 Papapanagiotou P. and Fleuriot J. (2019). A Pragmatic, Scalable Approach to Correctbyconstruction Process Composition Using Classical Linear Logic Inference. LogicBased Program Synthesis and Transformation (Postproceedings of LOPSTR 2018), LNCS Springer, Volume 11408, 7793.
 Fleuriot J., Wang D. and Calmet J. (Eds. 2018). Artificial Intelligence and Symbolic Computation. Lecture Notes in Artificial Intelligence, Volume 1110, Springer.
 Palmer J. and Fleuriot J. (2018) Mechanising an Independent Axiom System for Minkowski Spacetime. Proceedings of the 12th International Conference on Automated Deduction in Geometry, 6479.
 Morris I. and Fleuriot J. (2018). Towards a Mechanisation in Isabelle of Birkhoff’s Ruler and Protractor Geometry. Proceedings of the 12th International Conference on Automated Deduction in Geometry, 4663.
 Narboux J., Janicic P. and Fleuriot J. (2018). Computerassisted Theorem Proving in Synthetic Geometry. Chapter in the Handbook of Geometric Constraint Systems Principles (ISBN 9781498738910), 2144, Chapman and Hall/CRC, July 2018.
 Jiang Y., Papapanagiotou P. and Fleuriot J. (2018). Machine Learning for Automated Inductive Theorem Proving. Proceedings of the 13th International Artificial Intelligence and Symbolic Computation (AISC) Conference 2018, Lecture Notes in Artificial Intelligence, Volume 11110, 87103.
 Papapanagiotou P. and Fleuriot J. (2018). Correctbyconstruction Process Composition Using Classical Linear Logic Inference. Proceedings of LogicBased Program Synthesis and Transformation (LOPSTR) Symposium 2018.
 Wingfield L., Kulendran M., Khan O., Fleuriot J. (2017) Bringing Artificial Intelligence to Patient Care in Bariatric Surgery: A Feasibility Study. International Journal of Surgery, Volume 47 , S92.
 Papapanagiotou P. and Fleuriot J. (2017). WorkflowFM: A Logicbased Formal Verification Framework for Process Specification and Composition. Proceedings of the 26th International Conference on Automated Deduction (CADE 26). LNCS Volume 10395, 357370, Springer
 Dewanti, A., Papapanagiotou, P., Gilhooly, C., Fleuriot, J., Manataki, A. & Moss, L. (2017). Development of workflowbased guidelines for the care of burns in Scotland. Proceedings of the 9th International Conference eHealth 2017, 155158.
 Alexandru CA., Clutterbuck D., Papapanagiotou P., Fleuriot J. and Manataki A. (2017). A Step Towards the Standardisation of HIV Care Practices, 10th International Conference on Health Informatics.
Letter

Poon M.T.C., GaeteVillegas J., Brennan P. M., Fleuriot J. (2021). Letter to the Editor. Misconceptions in the field guide to big data for neurosurgeons. J Neurosurg. 29:12. doi: 10.3171/2020.10.JNS203834.
Formal Proof Libraries
 Smola F. and Fleuriot J. D. (2021). Hyperdual Numbers and Forward Differentiation. Arch. Formal Proofs.
 Fleuriot J. D. (2021). Real Exponents as the Limits of Sequences of Rational Exponents. Arch. Formal Proofs.
 Schmoetten R., Palmer J., Fleuriot J. D. (2021). Schutz’ Independent Axioms for Minkowski Spacetime. Arch. Formal Proofs.
Working Papers/Preprints
 Chevallier M. and Fleuriot J. (2021). Formalising the Foundations of Discrete Reinforcement Learning in Isabelle/HOL. arXiv:2112.05996.
 Schmoetten R., Palmer J. E., Fleuriot J. D. (2021). Towards Formalising Schutz’ Axioms for Minkowski Spacetime in Isabelle/HOL. arXiv:2108.10868.
 Charlton C. E., Poon M. T. C., Brennan P. M. and Fleuriot J. D. (2021). Interpretable Machine Learning Classifiers for Brain Tumour Survival Prediction. arXiv:2106.0942.
 MacKenzie C., Fleuriot J. and Vaughan J. (2021). An Evaluation of the Archive of Formal Proofs. arXiv:2104.01052.
 Scott P. and Fleuriot J. D. (2019). Where are the Natural Numbers in Hilbert’s Foundations of Geometry? arXiv:1911.07057.
Recent PhD Theses
 Yaqing Jiang (2019). Machine learning for inductive theorem proving, School of Informatics, University of Edinburgh.
Recent Masters Theses
 Richard Schmoetten (2020). Axiomatic Minkowski Spacetime in Isabelle/HOL. MSc in Informatics, School of Informatics, University of Edinburgh. One of the outstanding MSc theses of the academic year 201920 and Winner of the MSc in Informatics thesis prize. Supervisors: J. D. Fleuriot and J. Palmer
 Colleen Charlton (2020). Building an Interpretable MachineLearning Classifier for thePrediction of Brain TumourSurvival. MSc in Cognitive Science, School of Informatics, University of Edinburgh. One of the outstanding MSc theses of the academic year 201920. Supervisor: J. D. Fleuriot, in collaboration with Paul Brennan and Michael Poon.
 Anita Klementiev (2020). Evaluation of Process Mining Techniques for Modeling InHospital Patient Care Pathways Using the MIMICIII Dataset. MSc in Cognitive Science, School of Informatics, University of Edinburgh. MSc thesis awarded with Distinction. Supervisors: J. D. Fleuriot and C. Stables.
 Simon Thorogood (2019). Predicting Transplant and Patient Survival Following Liver Transplantation using Machine Learning. MSc in Data Science, School of Informatics, University of Edinburgh. One of the outstanding MSc theses of academic year 201819 and Winner of the Informatics MSc in Data Science thesis prize. Supervisor: J. D. Fleuriot, in collaboration with L. Wingfield and S. Knight.
 Callum Biggs O’May (2019). Investigating Brain Cancer Survival with Machine Learning. MSc in Artificial Intelligence, School of Informatics, University of Edinburgh. One of the outstanding MSc theses of academic year 201819. Supervisor: J. D. Fleuriot, in collaboration with Paul Brennan.
 Jessika Rockel (2019). Exploring Euler’s Foundations of Differential Calculus in Isabelle/HOL using Nonstandard Analysis. MSc in Computer Science, School of Informatics, University of Edinburgh. One of the outstanding MSc theses of academic year 201819. Supervisor: J. D. Fleuriot.
 Ka Wing Pang (2019). Exploring streams with Isabelle/HOL. MSc in Computer Science, School of Informatics, University of Edinburgh. MSc thesis awarded with Distinction. Supervisor: J. D. Fleuriot.