Dr Keefe Murphy

Mathematics and Statistics, Hamilton Institute

Lecturer

Logic House
130
(01) 708 4641

Biography

I am a statistician with primary research interests in developing methodologies for both supervised and unsupervised classification tasks involving complex, high-dimensional, mixed-type data, often in the presence of outliers and concomitant variables. Publications to date include work on Bayesian nonparametric mixtures of factor analysers, covariate-dependent parsimonious model-based clustering, and risk-stratification for multi-omic prostate cancer data. I am currently working on applications of novel distance-based clustering approaches for longitudinal categorical sequences, along with various extensions to the BART model, missing data modelling, multivariate count data, variable selection in mixtures-of-experts models, and variable importance in model-based clustering more generally. I take a keen interest in the computational implementation of statistical models and have authored the R packages IMIFA, MoEClust, and MEDseq - all of which are available on CRAN - and contributed to several others.

Research Interests

I have a broad range of research interests in the fields of Statistics, Data Science, and Machine Learning including, but not limited to; mixture models, latent variable models, model-based clustering and classification, Bayesian nonparametrics, shrinkage priors, applications to high-dimensional, mixed-type data, computational statistics, dimension reduction, sequence analysis, missing data mechanisms, multivariate count data, tree-based methods, non-parametric regression, variable selection, model selection, and model aggregation. Most of the research projects I have worked on involved a non-trivial computation aspect and I take a keen interest in distributing software implementations of my novel methodologies.

Peer Reviewed Journal

Year Publication
2024 Maia, M.; Murphy, K.; Parnell, A.C. (2024) 'GP-BART: A novel Bayesian additive regression trees approach using Gaussian processes'. Computational Statistics and Data Analysis, 190 . [Link] [DOI]
2024 Saqr, M.; López-Pernas, S.; Murphy, K. (2024) 'How group structure, members' interactions and teacher facilitation explain the emergence of roles in collaborative learning'. Learning and Individual Differences, 112 . [DOI]
2021 Murphy K.; Murphy T.B.; Piccarreta R.; Gormley I.C. (2021) 'Clustering longitudinal life-course sequences using mixtures of exponential-distance models'. Journal of the Royal Statistical Society. Series A, (Statistics in Society), 184 (4):1414-1451. [DOI] [Full-Text]
2020 Murphy K.; Murphy T.B. (2020) 'Gaussian parsimonious clustering models with covariates and a noise component'. Advances in Data Analysis and Classification, 14 (2):293-325. [DOI] [Full-Text]
2020 Murphy K.; Viroli C.; Gormley I.C. (2020) 'Infinite mixtures of infinite factor analysers'. Bayesian Analysis, 15 (3):937-963. [DOI] [Full-Text]
2020 Gilgunn, S.; Murphy, K.; Stöckmann, H.; Conroy, P.J.; Murphy, T.B.; Watson, R.W.G.; O'Kennedy, R.J.; Rudd, P.M.; Saldova, R. (2020) 'Glycosylation in Indolent, Significant and Aggressive Prostate Cancer by Automated High-Throughput N-Glycan Profiling'. International Journal of Molecular Sciences, 21 . [DOI] [Full-Text]
2020 Jalali A.; Foley, R.W.; Maweni, R.M.; Murphy, K.; Lundon, D.J.; Lynch, T.; Power, R.; O'Brien, F.; O'Malley, K.J.; Galvin, D.J.; Durkan, G.C.; Murphy, T.B.; Watson, R.W.G. (2020) 'A risk calculator to inform the need for a prostate biopsy: a rapid access clinic cohort'. BMC Medical Informatics and Decision Making, 20 (1). [DOI] [Full-Text]
2018 Murphy K.; Murphy T.B.; Boyce S.; Flynn L.; Gilgunn S.; O'Rourke, C.J.; Rooney, C.; Stöckmann, H.; Walsh, A.L.; Finn, S.; O'Kenndy, R.J.; O'Leary, J.; Pennington, S.R.; Perry, A.S.; Rudd, P.M.; Saldova, R.; Sheils, O.; Shields, D.C.; Watson, R.W.G. (2018) 'Integrating biomarkers across omic platforms: an approach to improve stratification of patients with indolent and aggressive prostate cancer'. Molecular Oncology, 12 (9). [DOI]
2017 Hanrahan K.; O'Neill, A.; Prencipe, M.; Bugler, J.; Murphy, L.; Fabre, A.; Puhr, M.; Culig, Z.; Murphy, K.; Watson, R.W.G. (2017) 'The role of epithelial-mesenchymal transition drivers ZEB1 and ZEB2 in mediating docetaxel-resistant prostate cancer'. Molecular Oncology, 11 (3). [DOI]
2016 Foley, R.W.; Maweni, R.M.; Gorman, L.; Murphy, K.; Lundon, D.J.; Durkan, G.; Power, R.; O'Brien, F.; O'Malley, K.J.; Galvin, D.J.; Murphy, T.B.; Watson, R.W.G. (2016) 'European Randomised Study of Screening for Prostate Cancer (ERSPC) risk calculators significantly outperform the Prostate Cancer Prevention Trial (PCPT) 2.0 in the prediction of prostate cancer: a multi-institutional study'. BJU International, 118 (5). [DOI]
2016 Foley, R.W.; Gorman, L.; Sharifi, N.; Murphy, K.; Moore, H.; Tuzova, A.V.; Perry, A.S.; Murphy, T.B.; Lundon, D.J.; Watson, R.W.G. (2016) 'Improving multivariable prostate cancer risk assessment using the Prostate Health Index'. BJU International, 117 (3). [DOI]
2015 Foley, R.W.; Lundon, D.J.; Murphy, K.; Murphy, T.B.; Galvin, D.J.; Watson, R.W.G. (2015) 'Predicting prostate cancer: analysing the clinical efficacy of prostate cancer risk calculators in a referral population'. Irish Journal of Medical Science, 184 (3). [DOI]

Computer Program

Year Publication
2020 Murphy, K.; Murphy, T.B.; Piccarreta, R.; Gormley, I.C. (2020) MEDseq: Mixtures of Exponential-Distance Models with Covariates. [Computer Program]
2020 Murphy K.; Murphy T.B. (2020) MoEClust: Gaussian Parsimonious Clustering Models with Covariates and a Noise Component. [Computer Program]
2020 Murphy K.; Viroli C.; Gormley I.C. (2020) IMIFA: Infinite Mixtures of Infinite Factor Analysers and Related Models. [Computer Program]

Book Chapter

Year Publication
2024 Murphy, K.; López-Pernas, S.; Saqr, M. (2024) 'Dissimilarity-Based Cluster Analysis of Educational Data: A Comparative Tutorial Using R' In: Learning Analytics Methods and Tutorials: A Practical Guide Using R. Cham : Springer. https://doi.org/10.1007/978-3-031-54464-4_8
2024 Scrucca, L.; Saqr, M.; López-Pernas, S.; Murphy, K. (2024) 'An Introduction and R Tutorial to Model-Based Clustering in Education via Latent Profile Analysis' In: Learning Analytics Methods and Tutorials: A Practical Guide Using R. Cham : Springer. https://doi.org/10.1007/978-3-031-54464-4_9
2024 Saqr, M.; López-Pernas, S.; Helske, S.; Durand, M.; Murphy, K.; Studer, M.; Ritschard, G. (2024) 'Sequence Analysis in Education: Principles, Technique, and Tutorial with R' In: Learning Analytics Methods and Tutorials: A Practical Guide Using R. Cham : Springer. https://doi.org/10.1007/978-3-031-54464-4_10
2024 Helske, J.; Helske, S.; Saqr, S.; López-Pernas, S.; Murphy, K. (2024) 'A Modern Approach to Transition Analysis and Process Mining with Markov Models in Education' In: Learning Analytics Methods and Tutorials: A Practical Guide Using R. Cham : Springer. https://doi.org/10.1007/978-3-031-54464-4_12
2024 López-Pernas, S.; Saqr, M.; Helske, S.; Murphy, K. (2024) 'Multi-Channel Sequence Analysis in Educational Research: An Introduction and Tutorial with R' In: Learning Analytics Methods and Tutorials. Cham : Springer. https://doi.org/10.1007/978-3-031-54464-4_13
Certain data included herein are derived from the © Web of Science (2024) of Clarivate. All rights reserved.

Honors and Awards

Date Title Awarding Body
01/06/2020 Distinguished Dissertation Award The Classification Society

Education

Start date Institution Qualification Subject
University College Dublin Doctor of Philosophy Statistics
University College Dublin Master of Science Statistics
University of Limerick Bachelor of Science Economics & Mathematics

Editorial / Academic Reviews

Amount Role From / To
Statistical Analysis and Data Mining Associate Editor -
Advances in Data Analysis and Classification Reviewer -
Annals of Applied Statistics Reviewer -
Australian and New Zealand Journal of Statistics Reviewer -
Bayesian Analysis Reviewer -
Communications in Statistics Part B: Simulation and Computation Reviewer -
Computational Statistics and Data Analysis Reviewer -
International Journal of Computer Applications in Technology Reviewer -
International Journal of Information and Education Technology Reviewer -
Journal of Classification Reviewer -
Journal of Computational and Graphical Statistics Reviewer -
Journal of Statistical Software Reviewer -
Methodology Reviewer -
Pattern Recognition Reviewer -
PLOS One Reviewer -
The R Journal Reviewer -
Scandinavian Journal of Statistics Reviewer -
Statistical Analysis and Data Mining Reviewer -
Statistics and Computing Reviewer -

Teaching Interests

I am currently lecturing modules on Advanced R Programming, Introduction to Data Science, and Nonparametric Statistics. Other courses I have previously taught include Design & Analysis of Experiments, Introduction to Statistics, Linear Models, Statistical Computing with R, Statistical Machine Learning, and Stochastic Processes.

Recent Students

Graduation date Name Degree
2024 Mateus Maia PhD