Dr Keefe Murphy
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, distance-based clustering models for longitudinal categorical sequences, risk-stratification for multi-omic prostate cancer data, and many applications of statistical machine learning methods in the field of learning analytics.
I am currently working on 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 also 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 | |
|---|---|---|
| 2025 | Prado, E.B.; Parnell, A.C.; Moral, R.A.; McJames, N.; O'Shea, A.; Murphy, K. (2025) 'Accounting for shared covariates in semiparametric Bayesian additive regression trees'. Annals of Applied Statistics, 19 (1):302-328. [DOI] | |
| 2025 | Urbas, S.; Finucane, K.; Gormley, I.C.; Murphy, K. (2025) 'Contributed Discussion on Sparse Bayesian factor analysis when the number of factors is unknown by Frühwirth-Schnatter, S., Hosszejni, D., and Lopes, H.F'. Bayesian Analysis, 20 (1):213-344. [DOI] | |
| 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'Kennedy, 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
Book Chapter
Certain data included herein are derived from the © Web of Science (2025) of Clarivate. All rights reserved.
Editorial / Academic Reviews
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.