discovery

UCD Institute for Discovery

UCD Discovery Institute - Research Publications 2023/24

Below is the list of research publications for the UCD Discovery Institute in the academic year 2023/24.



Chapter

Professor Anthony Brabazon

O’Neill, M., & Brabazon, A. (2024). Evolutionary Machine Learning in Finance. In Genetic and Evolutionary Computation (pp. 695-713). Springer Nature Singapore. doi:10.1007/978-981-99-3814-8_24

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Assoc Professor Kathleen Curran

Hagos, M. T., Belton, N., Killeen, R. P., Curran, K. M., & Mac Namee, B. (2023). Interpretable Weighted Siamese Network to Predict the Time to Onset of Alzheimer’s Disease from MRI Images. In Lecture Notes in Computer Science (pp. 391-403). Springer Nature Switzerland. doi:10.1007/978-3-031-47994-6_35

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Ma, S., Du, H., Curran, K. M., Lawlor, A., & Dong, R. (2024). Adaptive Curriculum Query Strategy for Active Learning in Medical Image Classification. In Lecture Notes in Computer Science (pp. 48-57). Springer Nature Switzerland. doi:10.1007/978-3-031-72120-5_5

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Dietlmeier, J., Garcia-Cabrera, C., Hashmi, A., Curran, K. M., & O’Connor, N. E. (2024). Cardiac MRI Reconstruction from Undersampled K-Space Using Double-Stream IFFT and a Denoising GNA-UNET Pipeline. In Unknown Book (Vol. 14507 LNCS, pp. 326-338). doi:10.1007/978-3-031-52448-6_31

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Garcia-Cabrera, C., Sánchez, E. A., Moreu, E., Curran, K. M., O’Connor, N. E., & McGuinness, K. (2024). Synthetic Balancing of Cardiac MRI Datasets. In Unknown Book (Vol. 14860 LNCS, pp. 353-365). doi:10.1007/978-3-031-66958-3_26

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Professor Nial Friel

Kaur, H., Rastelli, R., Friel, N., & Raftery, A. E. (2024). Latent Position Network Models. In The Sage Handbook of Social Network Analysis (pp. 526-541). Sage Publications Ltd. doi:10.4135/9781529614695.n36

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Professor Michael O'Neill

O’Neill, M., & Brabazon, A. (2024). Evolutionary Machine Learning in Finance. In Genetic and Evolutionary Computation (pp. 695-713). Springer Nature Singapore. doi:10.1007/978-981-99-3814-8_24

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Conference Paper

Assoc Professor Kathleen Curran

Noonan, K., Hearne, R., Gaffney, B., Sheehy, B., Mcveigh, N., Sekimoto, Y., et al. (2023). Differentiating diffuse cystic lung disease and emphysema cases from normal using Artificial Intelligence. In Imaging (pp. PA2292). European Respiratory Society. doi:10.1183/13993003.congress-2023.pa2292

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Hashmi, A., Dietlmeier, J., Curran, K. M., & O’Connor, N. E. (2024). Cardiac MRI Reconstruction with CMRatt: An Attention-Driven Approach. In European Signal Processing Conference (pp. 1666-1670).

 

Aleem, S., Wang, F., Maniparambil, M., Arazo, E., Dietlmeier, J., Curran, K., et al. (2024). Test-Time Adaptation with SaLIP: A Cascade of SAM and CLIP for Zero-shot Medical Image Segmentation. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (pp. 5184-5193). doi:10.1109/CVPRW63382.2024.00526

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Assoc Professor Neil Hurley

Singha Roy, A., D'Amico, E., Tragos, E., Lawlor, A., & Hurley, N. (2023). Scalable Deep Q-Learning for Session-Based Slate Recommendation. In Proceedings of the 17th ACM Conference on Recommender Systems, RecSys 2023 (pp. 877-882). doi:10.1145/3604915.3608843

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O’Reilly Morgan, D., Tragos, E., Geraci, J., Wang, Q., Hurley, N., Smyth, B., & Lawlor, A. (2024). A Hybrid Decentralised Learning Topology for Recommendations with Improved Privacy. In EuroMLSys 2024 - Proceedings of the 2024 4th Workshop on Machine Learning and Systems (pp. 161-168). doi:10.1145/3642970.3655841

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Hurley, N., Duriakova, E., Geraci, J., O’Reilly-Morgan, D., Tragos, E., Smyth, B., & Lawlor, A. (2024). ALS Algorithm for Robust and Communication-Efficient Federated Learning. In EuroMLSys 2024 - Proceedings of the 2024 4th Workshop on Machine Learning and Systems (pp. 56-64). doi:10.1145/3642970.3655842

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Professor Mohand Tahar Kechadi

Xu, C., & Kechadi, M. T. (2023). Fuzzy Deep Hybrid Network for Fake News Detection. In ACM International Conference Proceeding Series (pp. 118-125). doi:10.1145/3628797.3628971

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Phan, D. T. B., Le, P. V. L., Luong, N. H., Kechadi, T., & Ngo, H. Q. (2023). Domain Adaptation in Nested Named Entity Recognition From Scientific Articles in Agriculture. In ACM International Conference Proceeding Series (pp. 48-55). doi:10.1145/3628797.3628958

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Li, Y., Zainab, S. S. E., Dhelim, S., & Kechadi, M. T. (2024). Weather Data and Agro-climate Indices - Comparative Study. In ACM International Conference Proceeding Series (pp. 1-7). doi:10.1145/3651671.3651729

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Li, Y., Dhelim, S., & Kechadi, M. T. (2024). Predicting Winter Wheat Emergence and Stem Elongation Time using CNN. In ACM International Conference Proceeding Series (pp. 153-160). doi:10.1145/3651671.3651728

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Bimonte, S., Bellocchi, G., Pinet, F., Charrier, G., Sacharidis, D., Sakr, M., et al. (2024). Technological and Research Challenges in Data Engineering for Sustainable Agriculture. In Proceedings of the International Workshop on Big Data in Emergent Distributed Environments, BIDEDE 2024, in conjunction with the 2024 ACM SIGMOD/PODS Conference. doi:10.1145/3663741.3664786

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Dr Miguel Nicolau

Higgins, A., Nicolau, M., Flaherty, N., O'Neill, M., Munnelly, J., & McDermot, J. (2023). Strategies for “AI aware” assessment design/re-design. In Academic and Research Integrity Conference Ireland (pp. 1-6). Galway, Ireland.

 
Professor Michael O'Neill

Claret, R., O'Neill, M., Cotofrei, P., & Stoffel, K. (2024). Investigating Hyperparameter Optimization and Transferability for ES-HyperNEAT: A TPE Approach. In GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion (pp. 1879-1887). doi:10.1145/3638530.3664144

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Internet publication

Assoc Professor Kathleen Curran

Hagos, M. T., Belton, N., Curran, K. M., & Namee, B. M. (2023). Distance-Aware eXplanation Based Learning. IEEE.

 

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Journal article

Assoc Professor Nicolae Buchete

Buchete, N. -V., Cicha, I., Dutta, S., & Neofytou, P. (2024). Multiscale physics-based in silico modelling of nanocarrier-assisted intravascular drug delivery. Frontiers in Drug Delivery, 4. doi:10.3389/fddev.2024.1362660

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Assoc Professor Miguel Bustamante

Kumar, S., Crowley, C., Khan, M. F., Bustamante, M. D., Cahill, R. A., & Nolan, K. (2023). Understanding surgical smoke in laparoscopy through Lagrangian Coherent Structures. PLoS ONE, 18(11 November). doi:10.1371/journal.pone.0293287

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Pezzi, A., Comito, T., Bustamante, M. D., & Onorato, M. (2023). Three- and four-wave resonances in the nonlinear quadratic Kelvin lattice. Communications in Nonlinear Science and Numerical Simulation, 127. doi:10.1016/j.cnsns.2023.107548

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Chang, Z. W., Hao, W. C., Bustamante, M., & Liu, X. (2024). Constructing Hopf Insulator from Geometric Perspective of Hopf Invariant. Chinese Physics Letters, 41(3). doi:10.1088/0256-307X/41/3/037302

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Protas, B., Kang, D., & Bustamante, M. D. (2024). Alignments of triad phases in extreme one-dimensional Burgers flows. Physical Review E, 109(5). doi:10.1103/PhysRevE.109.055104

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Amirfazli, A., Bustamante, M. D., Hu, Y., & Ó Náraigh, L. (2024). Bounds on the spreading radius in droplet impact: The inviscid case. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 480(2294). doi:10.1098/rspa.2023.0760

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Assoc Professor Eimear Byrne

Bonini, M., Borello, M., & Byrne, E. (2023). Saturating systems and the rank-metric covering radius. Journal of Algebraic Combinatorics, 58(4), 1173-1202. doi:10.1007/s10801-023-01269-9

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Byrne, E., Ceria, M., Ionica, S., & Jurrius, R. (2024). Weighted Subspace Designs from q-Polymatroids. Journal of Combinatorial Theory. Series A, 201. doi:10.1016/j.jcta.2023.105799

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Byrne, E., & Cotardo, G. (2024). Constructions of perfect bases for classes of 3-tensors. Linear Algebra and Its Applications, 683, 1-30. doi:10.1016/j.laa.2023.11.019

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Alfarano, G. N., & Byrne, E. (2024). The cyclic flats of a q-matroid. Journal of Algebraic Combinatorics, 60(1), 97-126. doi:10.1007/s10801-024-01321-2

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Assoc Professor Kathleen Curran

Bartels, H. C., O’Doherty, J., Wolsztynski, E., Brophy, D. P., MacDermott, R., Atallah, D., et al. (2023). Radiomics-based prediction of FIGO grade for placenta accreta spectrum. European Radiology Experimental, 7(1). doi:10.1186/s41747-023-00369-2

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Bartels, H. C., O’Doherty, J., Wolsztynski, E., Brophy, D. P., MacDermott, R., Atallah, D., et al. (2023). Correction: Radiomics-based prediction of FIGO grade for placenta accreta spectrum (European Radiology Experimental, (2023), 7, 1, (54), 10.1186/s41747-023-00369-2). European Radiology Experimental, 7(1). doi:10.1186/s41747-023-00397-y

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Foessl, I., Ackert-Bicknell, C. L., Kague, E., Laskou, F., Jakob, F., Karasik, D., et al. (2024). A perspective on muscle phenotyping in musculoskeletal research. Trends in Endocrinology and Metabolism, 35(6), 478-489. doi:10.1016/j.tem.2024.01.004

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Belton, N., Hagos, M. T., Lawlor, A., & Curran, K. M. (2024). Towards a unified approach for unsupervised brain MRI Motion Artefact Detection with few shot Anomaly Detection. Computerized Medical Imaging and Graphics, 115. doi:10.1016/j.compmedimag.2024.102391

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Bartels, H. C., Hameed, S., Young, C., Nabhan, M., Downey, P., Curran, K. M., et al. (2024). Biological comparisons between pre-eclampsia and placenta accreta spectrum. npj Women's Health, 2(1). doi:10.1038/s44294-024-00034-y

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Professor Frederic Dias

Kokina, T., Peláez-Zapata, D. S., Murphy, T. B., & Dias, F. (2023). Improving the sea state forecasts by using local wave observations and the ensembleBMA software. Environmental Data Science, 2. doi:10.1017/eds.2023.31

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Liu, H., Liu, P. L. F., & Dias, F. (2023). Special topic on Physics and Modeling of Tsunamis. Physics of Fluids, 35(11). doi:10.1063/5.0182606

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Wu, Q., Feng, X., Dong, Y., & Dias, F. (2023). On the behavior of higher harmonics in the evolution of nonlinear water waves in the presence of abrupt depth transitions. Physics of Fluids, 35(12). doi:10.1063/5.0173173

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Støle-Hentschel, S., Catalán, P. A., Streßer, M., Horstmann, J., & Dias, F. (2024). Observations of Shoaling and Breaking Waves in Shallow Water with Different Coherent X-Band Radars. IEEE Transactions on Geoscience and Remote Sensing, 62, 1-18. doi:10.1109/TGRS.2024.3373785

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Ancellin, M., Marchand, P., & Dias, F. (2024). Towards High-Performance Linear Potential Flow BEM Solver with Low-Rank Compressions. Energies, 17(2). doi:10.3390/en17020372

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Warby, C., Dias, F., Schoefs, F., & Pakrashi, V. (2024). An ecologically aware modification of the Morison's equation for long term marine growth effects. Mechanics Research Communications, 139. doi:10.1016/j.mechrescom.2024.104293

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Peláez-Zapata, D., Pakrashi, V., & Dias, F. (2024). Ocean Wave Directional Distribution from GPS Buoy Observations off the West Coast of Ireland: Assessment of a Wavelet-Based Method. Journal of Atmospheric and Oceanic Technology, 41(8), 749-765. doi:10.1175/jtech-d-23-0058.1

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Renzi, E., Bergin, C., Kokina, T., Pelaez-Zapata, D. S., Giles, D., & Dias, F. (2024). Recent meteorological tsunamis and other anomalous tidal surge events in western Europe. doi:10.5194/ems2024-184

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Professor Nial Friel

Rastelli, R., Maire, F., & Friel, N. (2024). Computationally efficient inference for latent position network models. Electronic Journal of Statistics, 18(1), 2531-2570. doi:10.1214/24-EJS2256

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Mulder, J., Friel, N., & Leifeld, P. (2024). Bayesian testing of scientific expectations under exponential random graph models. Social Networks, 78, 40-53. doi:10.1016/j.socnet.2023.11.004

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Professor Claire Gormley

Frizzarin, M., Miglior, F., Berry, D. P., Gormley, I. C., & Baes, C. F. (2023). Usefulness of mid-infrared spectroscopy as a tool to estimate body condition score change from milk samples in intensively fed dairy cows. Journal of Dairy Science, 106(12), 9115-9124. doi:10.3168/jds.2023-23290

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Tavernier, E., Gormley, I. C., Delaby, L., McParland, S., O'Donovan, M., & Berry, D. P. (2023). Cow-level factors associated with nitrogen utilization in grazing dairy cows using a cross-sectional analysis of a large database. Journal of Dairy Science, 106(12), 8871-8884. doi:10.3168/jds.2023-23606

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O’Reilly, D., Murphy, C. A., Moore, C. M., Ní Áinle, F., Gormley, I. C., Morrell, C. N., et al. (2024). Markers of platelet activation foR identification of late onset sEpsis in infaNTs: PARENT study protocol. Pediatric Research, 95(3), 852-856. doi:10.1038/s41390-023-02812-x

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Tavernier, E., Gormley, I. C., Delaby, L., O'Donovan, M., & Berry, D. P. (2024). Genetic covariance components for measures of nitrogen utilization in grazing dairy cows. Journal of Dairy Science, 107(4), 2231-2240. doi:10.3168/jds.2023-24117

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Gwee, X. Y., Gormley, I. C., & Fop, M. (2024). Variational inference for the latent shrinkage position model. Stat, 13(2). doi:10.1002/sta4.685

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Assoc Professor Russell Higgs

Higgs, R. J., Finnegan, C., & Healy, D. (2024). Groups with three projective characters. Communications in Algebra, 52(3), 1063-1083. doi:10.1080/00927872.2023.2255670

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Higgs, R. J. (2024). FROBENIUS–SCHUR INDICATORS FOR PROJECTIVE CHARACTERS WITH APPLICATIONS. Bulletin of the Australian Mathematical Society. doi:10.1017/S0004972724000571

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Higgs, R. J. (2024). Projective Character Values on Real and Rational Elements. Bulletin of the Australian Mathematical Society. doi:10.1017/S0004972724000030

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Professor Mohand Tahar Kechadi

Xu, C., & Kechadi, M. T. (2024). An Enhanced Fake News Detection System With Fuzzy Deep Learning. IEEE Access, 12, 88006-88021. doi:10.1109/ACCESS.2024.3418340

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Bansal, Y., Lillis, D., & Kechadi, M. T. (2024). Correction to: A neural meta model for predicting winter wheat crop yield (Machine Learning, (2024), 10.1007/s10994-023-06455-1). Machine Learning, 113(5), 3353. doi:10.1007/s10994-024-06535-w

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Bansal, Y., Lillis, D., & Kechadi, M. T. (2024). A neural meta model for predicting winter wheat crop yield. Machine Learning, 113(6), 3771-3788. doi:10.1007/s10994-023-06455-1

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Assoc Professor Vladimir Lobaskin

Štrancar, J., Urbancic, I., Stoeger, T., Lobaskin, V., & Vogel, U. (2023). P17-28: From automated early mode-of-action determination to Chronic Inflammation Prediction for Inhaled Particles. Toxicology Letters, 384, S218. doi:10.1016/s0378-4274(23)00769-5

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Lobaskin, V., Subbotina, J., & Rouse, I. (2023). Computational modelling of bionano interface. EPL, 143(5). doi:10.1209/0295-5075/acf33f

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Amini, P. M., Rouse, I., Subbotina, J., & Lobaskin, V. (2024). Multiscale modelling of biomolecular corona formation on metallic surfaces. Beilstein Journal of Nanotechnology, 15, 215-229. doi:10.3762/bjnano.15.21

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Serrano, B. A., Gheorghe, L. C., Exner, T. E., Resch, S., Wolf, C., Himly, M., et al. (2024). The role of FAIR nanosafety data and nanoinformatics in achieving the UN sustainable development goals: the NanoCommons experience. RSC Sustainability, 2(5), 1378-1399. doi:10.1039/d3su00148b

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Mortensen, H. M., Amos, J. D., Exner, T. E., Flores, K., Harper, S., Jarabek, A. M., et al. (2024). NNI nanoinformatics conference 2023: Movement toward a common infrastructure for federal nanoEHS data computational toxicology: Short communication. Computational Toxicology, 30. doi:10.1016/j.comtox.2024.100316

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Professor Gary McGuire

Gow, R., & McGuire, G. (2023). On Galois groups of linearized polynomials related to the general linear group of prime degree. Journal of Number Theory, 253, 368-377. doi:10.1016/j.jnt.2023.06.018

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Barbero-Lucas, B., Hernando, F., Martín-Cruz, H., & McGuire, G. (2024). MDS, Hermitian almost MDS, and Gilbert–Varshamov quantum codes from generalized monomial-Cartesian codes. Quantum Information Processing, 23(3). doi:10.1007/s11128-024-04297-x

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Gow, R., & McGuire, G. (2024). On Galois groups of linearized polynomials related to the special linear group of prime degree. Linear Algebra and Its Applications, 693, 49-62. doi:10.1016/j.laa.2023.03.004

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Professor Brendan Murphy

Monacelli, G., Zhang, L., Schlee, W., Langguth, B., Ward, T. E., & Murphy, T. B. (2023). Adaptive data collection for intraindividual studies affected by adherence. Biometrical Journal, 65(7). doi:10.1002/bimj.202200203

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Alkema, L., Murphy, T. B., & Raftery, A. E. (2023). Interview With Adrian Raftery. International Statistical Review, 91(3), 349-367. doi:10.1111/insr.12557

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Duggan, J., Andrade, J., Murphy, T. B., Gleeson, J. P., Walsh, C., & Nolan, P. (2024). An age-cohort simulation model for generating COVID-19 scenarios: A study from Ireland's pandemic response. European Journal of Operational Research, 313(1), 343-358. doi:10.1016/j.ejor.2023.08.011

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García-Escudero, L. A., Ingrassia, S., & Murphy, T. B. (2024). Special issue on “advances in models and learning for clustering and classification”. Advances in Data Analysis and Classification, 18(1), 1-4. doi:10.1007/s11634-024-00584-8

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Berrettini, M., Galimberti, G., Ranciati, S., & Murphy, T. B. (2024). Identifying Brexit voting patterns in the British house of commons: an analysis based on Bayesian mixture models with flexible concomitant covariate effects. Journal of the Royal Statistical Society. Series C: Applied Statistics, 73(3), 621-638. doi:10.1093/jrsssc/qlae004

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Dr Miguel Nicolau

Mauceri, S., Sweeney, J., Nicolau, M., & Mcdermott, J. (2024). Dissimilarity-Preserving Representation Learning for One-Class Time Series Classification. IEEE Transactions on Neural Networks and Learning Systems, 35(10), 13951-13962. doi:10.1109/TNNLS.2023.3273503

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Assoc Professor Lennon Ó Náraigh

Náraigh, L. I., & Mairal, J. (2023). Analysis of the spreading radius in droplet impact: The two-dimensional case. Physics of Fluids, 35(10). doi:10.1063/5.0169274

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Pang, K. E., Cuvillier, C., Kita, Y., & Náraigh, L. (2024). Flow stability in shallow droplets subject to localized heating of the bottom plate. Physical Review Fluids, 9(1). doi:10.1103/PhysRevFluids.9.014003

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Ó Náraigh, L. (2024). A mathematical framework for spatio-temporal control in industrial drying. International Journal of Modeling, Simulation, and Scientific Computing, 15(1). doi:10.1142/S1793962324500193

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Amirfazli, A., Bustamante, M. D., Hu, Y., & Ó Náraigh, L. (2024). Bounds on the spreading radius in droplet impact: The inviscid case. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 480(2294). doi:10.1098/rspa.2023.0760

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Professor Adrian Ottewill

Arrechea, J., Breen, C., Ottewill, A., & Taylor, P. (2023). Renormalized stress-energy tensor for scalar fields in Hartle-Hawking, Boulware, and Unruh states in the Reissner-Nordström spacetime. Physical Review D, 108(12). doi:10.1103/PhysRevD.108.125004

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Assoc Professor Gianluca Pollastri

Gillani, M., & Pollastri, G. (2024). SCLpred-ECL: Subcellular Localization Prediction by Deep N-to-1 Convolutional Neural Networks. International Journal of Molecular Sciences, 25(10). doi:10.3390/ijms25105440

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Other

Professor Frederic Dias

Calo, L. G., Bennis, A. -C., Boutet, M., & Dias, F. (2024). Τοwards a unified mοdelling οf wave-current-turbulence interactiοns in three dimensiοns: applicatiοn tο Alderney Race (France) and Gregοry Sound (Ιreland) . doi:10.5194/egusphere-egu24-9107

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Preprint

Assoc Professor Eimear Byrne

Byrne, E., Johnston, R. D., Kilroy, D., & Bhattacharjee, S. (2024). <i>An arch worth revisiting:</i>A study on the feline humeral supracondylar foramen and its evolutionary significance. doi:10.1101/2024.02.25.581957

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Assoc Professor Kathleen Curran

Bartels, H. C., Hameed, S., Young, C., Nabhan, M., Downey, P., Curran, K. M., et al. (2024). Spatial proteomics and transcriptomics of placenta accreta spectrum. doi:10.1101/2024.03.21.585167

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Professor Claire Gormley

O’Grady, J., McHugo, G., Ward, J., Hall, T., Faherty O’Donnell, S., Correia, C., et al. (2024). Integrative genomics sheds light on the immunobiology of tuberculosis in cattle. doi:10.1101/2024.02.27.582295

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Assoc Professor Vladimir Lobaskin

Mosaddeghi Amini, P., Rouse, I., Subbotina, J., & Lobaskin, V. (2023). Multiscale modelling for biomolecular corona formation on metallic surfaces. doi:10.3762/bxiv.2023.45.v1

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Assoc Professor Lennon Ó Náraigh

Vizcaíno García, P., Bustamante, M., Ó Náraigh, L., Herterich, J., & Keenahan, J. (n.d.). Understanding the effects of high-turbulence flow on 5:1 bluff bodies through computational simulation. doi:10.2139/ssrn.4917598

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Assoc Professor Gianluca Pollastri

Meng, D., & Pollastri, G. (2024). PUNCH2: explore the strategy for Intrinsically Disordered Protein predictor. doi:10.1101/2024.10.03.616458

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Software / Code

Professor Claire Gormley

Gormley, I., Majumdar, K., Silva, R., Perry, A. S., Watson, R. W., Rau, A., et al. (2023). betaclust: A Family of Beta Mixture Models for Clustering Beta-Valued DNA Methylation Data [Computer Software]. Retrieved from https://cran.r-project.org/web/packages/betaclust/index.html

 

Gormley, I., Fop, M., & Xian Yao, G. (2023). LSPM: a set of latent shrinkage position models for network data [Computer Software]. Retrieved from https://gitlab.com/gwee95/lspm

 

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