Big Data group publications

Selected publications from Big Data group members
Hands typing at a laptop computer.
Selected publications from members of the Big Data group.

Books and edited collections

  1. Walter M. J., Manikowski P. L., Craven M. J., Walker D. J. (2024). Explaining Optimisation of Offshore Wind Farms using Metaheuristics. (In press), Springer.
  2. Wei Y. (2024) Meta-analysis and survival analysis in healthcare: methods, applications and impact, invited book chapter, More UK Success Stories in Industrial Mathematics, in press, Springer.

Refereed conference contributions

  1. Walter M. J., Walker D. J., Craven M. J. (2022). An Explainable Visualisation of the Evolutionary Search Process, in: ECXAI (Evolutionary Computation and Explainable AI Workshop of GECCO 2022), ACM, 1794-1802.
  2. Dang, H. V., Phuong, T. V. X., Nguyen, T. D., & Hoang, T. (2022, December). ZAC: Efficient Zero-Knowledge Dynamic Universal Accumulator and Application to Zero-Knowledge Elementary Database. In 2022 IEEE 4th International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS-ISA) (pp. 248-257). IEEE.
  3. Gkountelos D, Kokhazadeh M, Bournas C, Keramidas G & Kelefouras V (2023) 'Towards Highly Compressed CNN Models for Human Activity Recognition in Wearable Devices' 2023 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA) 9-/-0/20239-/-0/2023IEEE , DOI
  4. Anthimopulos T, Keramidas G, Kelefouras V & Stamoulis I (2023) 'A Comparative Study of Neural Network Compilers on ARMv8 Architecture' Architecture of Computing Systems Springer Nature Switzerland 18-33
  5. Kokhazadeh M, Keramidas G, Kelefouras V & Stamoulis I (2022) 'A Design Space Exploration Methodology for Enabling Tensor Train Decomposition in Edge Devices' International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS), Best Paper Award
  6. Masing L, Dorr T, Schade F, Becker J, Keramidas G, Antonopoulos CP, Mavropoulos M, Tiganourias E, Kelefouras V & Antonopoulos K (2022) 'XANDAR: Exploiting the X-by-Construction Paradigm in Model-based Development of Safety-critical Systems' 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE) 3-/-0/20223-/-0/2022IEEE , DOI Open access
  7. Tobias Dörr, Florian Schade, Leonard Masing, Jürgen Becker, Georgios Keramidas, Christos P Antonopoulos, Michail Mavropoulos, Vasilios Kelefouras, Nikolaos Voros, ‘Safety by Construction: Pattern-Based Application of Safety Mechanisms in XANDAR’, IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 2022
  8. Masing L, Dorr T, Schade F, Becker J, Keramidas G, Antonopoulos CP, Mavropoulos M, Tiganourias E, V Kelefouras & Antonopoulos K (2022) 'XANDAR: Exploiting the X-by-Construction Paradigm in Model-based Development of Safety-critical Systems' 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE) 3-/-0/20223-/-0/2022IEEE
  9. Fahad Siddiqui, Rafiullah Khan, Kieran McLaughlin, Sakir Sezer, Leonard Masing, Tobias Dörr, Florian Schade, Jürgen Becker, Alexander Ahlbrecht, Wanja Zaeske, Umut Durak, Nico Adler, Andreas Sailer, Raphael Weber, Thomas Wilhelm, Geza Nemeth, Victor Morales, Paco Gomez, Georgios Keramidas, Christos P. Antonopoulos, Michail Mavropoulos, Vasilios Kelefouras, Konstantinos Antonopoulos, Nikolaos Voros, Christos Panagiotou, Dimitris Karadimas, ‘XANDAR: A holistic Cybersecurity Engineering Process for Safety-critical and Cyber-physical Systems’, 2022 IEEE 95th Vehicular Technology Conference (VTC2022-Spring)
  10. Karim Djemame, Vasilios Kelefouras. Evaluation of Language Runtimes in Open-Source Serverless Platforms. 12th International Conference on Cloud Computing and Services Science (CLOSER 2022), 27-29 April 2022
  11. Abdelmotaleb H., Wojtys M., McNeile C. (2023) GSDMM model evaluation techniques with application to British telecom data. Proceedings of the 5th International Conference on Statistics: Theory and Applications (ICSTA'23), DOI: 10.11159/icsta23.116.
  12. Sheikhi, A., Dalla Valle, L. and Mesiar, R. (2023) Copula-based change point detection in nonstationary multivariate time series of mixture marginals, Proceedings of the 40th Linz Seminar on Fuzzy Set Theory - Copulas Theory and Applications, Linz, Austria, pp. 85-88, ISBN 978-3-903480-02-5.
  13. Agosto, A., Dalla Valle, L. and De Giuli, M.E. (2022) Extreme dependence in the energy market: a Mixture copula-ARJI-GARCH model, Proceedings of the European Conference on Stochastic Optimization 2020 and Computational Management Science 2022 (ECSO CMS 2022), Venice, Italy.
  14. Dalla Valle, L., Kreuzer, A. and Czado, C. (2022) Environmental Risk: A Bayesian Non-linear State Space Copula Model to Predict Air Pollution in Beijing, Proceedings of the 9th International Conference on Risk Analysis (ICRA9), Perugia, Italy.
  15. Megan Courtman, Mark Thurston, Lucy McGavin, Camille Carroll, LingfenSun, Emmanuel Ifeachor, Stephen Mullin. (2023) Explainable deep learning based detection of Parkinson’s changes in MRI brain scans. 2023 International Congress of Movement Disorder, August 27-31, 2023. Copenhagen, Denmark.
  16. M. Courtman, M. Thurston, L. McGavin, C. Carroll, L. Sun, E. Ifeachor, S. Mullin. (AD/PD 2023) Artificial intelligence based detection of Parkinson’s disease in magnetic resonance imaging brain scans. International conference on Alzheimer’s and Parkinson’s diseases and related neurological disorders 28/03/2023 - 01/04/2023, Gothenburg , Sweden.
  17. Kocer BB, Orr L, Stephens B, Kaya YF, Buzykina T, Khan A & Kovac M (2022) 'An Intelligent Aerial Manipulator for Wind Turbine Inspection and Repair' 2022 UKACC 13th International Conference on Control (CONTROL) 4-/-0/20224-/-0/2022IEEE , DOI Open access. Awarded Best extended abstract.
  18. Day C, McEachen L, Khan A, Sharma S & Masala G (2019) 'Pedestrian Recognition and Obstacle Avoidance for Autonomous Vehicles using Raspberry Pi' IntelliSys 2019 , DOI Open access
  19. Biju, G., Khan A, Walker W., Qadri, S, Hasan, Q., Mahmood, K and Hanan, A. Identification of Cotton Leaf Curl Disease Using CNN and Vision Transformer, IntelliSys 2023, Intelligent Systems & Application, Chapter 44.  
  20. Best, O., Khan, A., Sharma S., Collins K. and Gianni, M. Wind Turbine Surface Damage Detection using YOLOv7 with Slicing Aided Hyper Inference (SAHI). IntelliSys 2023, Intelligent Systems & Applications.
  21. Anvekar, T. and Bazazian, D. (2023). GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 4178-4187). DOI Open Access. 

Academic peer-reviewed journal papers

  1. Scoble L., Ussher S. J., Fitzsimons M. F., Ansell L., Craven M. J., Fyfe R. M. (2024). Optimisation of classification methods to differentiate morphologically-similar pollen grains from FT-IR spectra, Review of Palaeobotany and Palynology 321, 105041. https://doi.org/10.1016/j.revpalbo.2023.105041.
  2. Stander, J. (2023) Is Rome becoming the ‘Infernal City’.  Significance Magazine.  https://significancemagazine.com/is-rome-becoming-the-infernal-city/
  3. Cardinali, A. (2023). Costationary Whitenoise Processes and Local Stationarity Testing. Contributions to Statistics: Theory and Applications of Time Series Analysis. (In press), Springer (ISBN: 978-3-031-40208-1)
  4. Alotaibi T. S., Dalla Valle L., Craven M. J. (2022). The Worst Case GARCH-Copula CVaR Approach for Portfolio Optmisation: Evidence from Financial Markets, Journal of Risk and Financial Management 15 (10), 482.
  5. Walter M. J., Walker D. J., Craven M. J. (2022). Visualising Population Dynamics to Examine Algorithm Performance, IEEE Transactions on Evolutionary Computation 26 (6), 1501-1510.
  6. Wei Y, Wojtys M, Sorrell L & Rowe P (2023) Bivariate copula regression models for semi-competing risks, Statistical Methods in Medical Research. https://journals.sagepub.com/doi/10.1177/09622802231188516 
  7. Riley S., Tan K., Tse W., Connor A. and Wei Y. (2023) Validation of kidney donor risk index for predicting transplant survival outcomes in the UK population: a comparison of methods, Diagnostic and Prognostic Research.
  8. Horne E.M.F., Hulme W.J., Keogh R.H., Palmer T.M., Williamson E.J., Parker E.P.K., Walker V., Knight R., Wei Y., Taylor K., Fisher L., Morley J., Mehrkar A., Dillingham I., Bacon S.C.J., Goldacre B., Sterne J.A.C. (2023) Challenges in estimating waning effectiveness of two doses of BNT162b2 and ChAdOx1 COVID-19 vaccines beyond six months: an OpenSAFELY cohort study using linked electronic health records, American Journal of Epidemiology.
  9. Riley S., Zhang Q., Tse W., Connor A. and Wei Y. (2022) Using information available at the time of donor offer to predict survival outcomes in kidney transplant recipients: a systematic review of methodology, Transplant International.
  10. Prestige E., Stander J. and Wei Y. (2022) COVID lockdowns in the UK: Estimating their effects on transmission, Significance, 19(2), 14 – 18. 
  11. Sorrell L., Wei Y., Wojtys M. and Rowe P. (2022) Estimating the correlation between semi-competing risk survival endpoints, Biometrical Journal, 64(1), 131-145. 
  12. Al-Kaabawi Z., Wei Y., and Moyeed R. (2022) Bayesian hierarchical models for linear networks, Journal of Applied Statistics, 49:6, 1421-1448. 
  13. Y Shtyrov, A Efremov, A Kuptsova, T Wennekers, B Gutkin, M Garagnani (2023) Breakdown of category-specific word representations in a brain-constrained neurocomputational model of semantic dementia. Scientific Reports.
  14. D Dobric, A Pech, B Ghita, T Wennekers (2022) On the importance of the newborn stage when learning patterns with the Spatial Pooler. Springer Nature Computer Science 3 (2), 179.
  15. F Pulvermüller, R Tomasello, MR Henningsen-Schomers, T Wennekers (2021) Biological constraints on neural network models of cognitive function. Nature Reviews Neuroscience 22 (8), 488-502.
  16. L. Ansell and L. Dalla Valle, A new data integration framework for Covid-19 social media information, Scientific Reports, 13(1), 2023
  17. L. Ansell and L. Dalla Valle, Social Media Integration of Flood Data: A Vine Copula-Based Approach, Journal of Environmental Informatics, 36(2), 2022
  18. Kelefouras V & Keramidas G (2023) 'Design and Implementation of Deep Learning 2D Convolutions on modern CPUs' IEEE Transactions on Parallel and Distributed Systems, 2023
  19. Kelefouras V & Keramidas G (2022) 'Design and Implementation of 2D Convolution on x86/x64 Processors' IEEE Transactions on Parallel and Distributed Systems, 2022
  20. Kelefouras V & Djemame K (2022) 'Workflow Simulation and Multi-Threading Aware Task Scheduling for Heterogeneous Computing' Journal of Parallel and Distributed Computing (Elsevier)
  21. Kelefouras V, Djemame K, Keramidas G & Voros N (2022) 'A methodology for efficient tile size selection for affine loop kernels' International Journal of Parallel Programming, Springer
  22. D Kolosov, V Kelefouras, P Kourtessis, I Mporas, ‘Contactless Camera-Based Heart Rate and Respiratory Rate Monitoring Using AI on Hardware’, MDPI Sensors, 2023  
  23. M Al-Saadi, A Khan, V Kelefouras, DJ Walker, B Al-Saadi, ‘SDN-Based Routing Framework for Elephant and Mice Flows Using Unsupervised Machine Learning’, MDPI Network, 218-238, 2023  
  24. Dimitrios Kolosov, Vasilios Kelefouras, Pandelis Kourtessis, Iosif Mporas, 'Anatomy of Deep Learning Image Classification and Object Detection on Commercial Edge Devices: A Case Study on Face Mask Detection', IEEE Access, 2022  
  25. M Kokhazadeh, G Keramidas, V Kelefouras, I Stamoulis, ‘A Practical Approach for Employing Tensor Train Decomposition in Edge Devices’, has been accepted in the Journal of Parallel Programming, Springer, 2023
  26. Fermilab Lattice, H.P.Q.C.D., Collaborations, M.I.L.C., Bazavov, A., Davies, C., DeTar, C., El-Khadra, A.X., Gámiz, E., Gottlieb, S., Jay, W.I., Jeong, H. and Kronfeld, A.S., 2023, McNeile. Light-quark connected intermediate-window contributions to the muon g− 2 hadronic vacuum polarization from lattice QCD. Physical Review D, 107(11), p.114514.
  27. C. T. H. Davies, McNeile et al., [Fermilab Lattice, MILC and HPQCD], ``Windows on the hadronic vacuum polarization contribution to the muon anomalous magnetic moment,'' Phys. Rev. D 106 (2022) no.7, 074509, doi:10.1103/PhysRevD.106.074509 [arXiv:2207.04765 [hep-lat]].
  28. H. Abdelmotaleb, M. Wojtys, C. McNeile (2023) “A comparison of a novel optimized GSDMM Model with K means clustering for topic modelling of free text” Journal of Machine Intelligence and Data Science. Accepted.  
  29. Kreuzer, A., Dalla Valle, L. and Czado, C. (2023) Bayesian Multivariate Nonlinear State Space Copula Models. Computational Statistics and Data Analysis, Vol. 188, 107820, ISSN: 0167-9473, DOI: https://doi.org/10.1016/j.csda.2023.107820.
  30. Agosto, A., Dalla Valle, L. and De Giuli, M.E. (2023) How do renewable and non-renewable co-move? Fresh evidence from the European energy market via ARJI-GARCH copula model. Mathematical Methods in Economics and Finance, Vol. 15/16, No. 1, 2020/2021, pp. 35-52, ISSN: 1971-6419, http://www.unive.it/m2ef/.
  31. Barone, R. and Dalla Valle, L. (2023) Bayesian Nonparametric Modelling of Conditional Multidimensional Dependence Structures. Journal of Computational and Graphical Statistics, Vol. 32, No. 4, pp. 1361-1370, ISSN: 1537-2715, DOI: https://doi.org/10.1080/10618600.2023.2173604.
  32. Kreuzer, A., Dalla Valle, L. and Czado, C. (2022) A Bayesian Non-linear State Space Copula Model to Predict Air Pollution in Beijing. Journal of the Royal Statistical Society-Series C, Vol. 71, No. 3, pp. 613-638, ISSN: 1467-9876, DOI: https://doi.org/10.1111/rssc.12548.  
  33. Grazian, C., Dalla Valle, L. and Liseo, B. (2022) Approximate Bayesian Conditional Copulas. Computational Statistics and Data Analysis, Vol. 169, 107417, ISSN: 0167-9473, DOI: https://doi.org/10.1016/j.csda.2021.107417.   
  34. Courtman, M., Thurston, M., McGavin, L., Caroll, C., Sun, L., Ifeachor, E., & Mullin, S. (2022). 095 Artificial Intelligence based detection of Parkinson’s disease in magnetic resonance imaging brain scans. Journal of Neurology, Neurosurgery & Psychiatry, 93, e2.45. https://doi.org/10.1136/jnnp-2022-abn2.139  
  35. Raj ANJ, Zhu H, Khan A, Zhuang Z, Yang Z, Mahesh VGV & Karthik G (2021) 'ADID-UNET—a segmentation model for COVID-19 infection from lung CT scans' PeerJ Computer Science 7, Publisher Site , DOI Open access
  36. Mounsey A, Khan A & Sharma S (2021) 'Deep and Transfer Learning Approaches for Pedestrian Identification and Classification in Autonomous Vehicles' Electronics 10, (24) 3159-3159 , DOI Open access.
  37. Belton A, Guillot D, Khare A & Putinar M (2023) 'Totally positive kernels, Pólya frequency functions, and their transforms' Journal d'Analyse Mathématique 150, (1) 83-158 , DOI
  38. Belton A, Guillot D, Khare A & Putinar M (2022) 'Hirschman–Widder densities' Applied and Computational Harmonic Analysis 60, 396-425 , DOI
  39. Belton A, Guillot D, Khare A & Putinar M (2022) 'Matrix compression along isogenic blocks' Acta Scientiarum Mathematicarum 88, (1-2) 417-448 , DOI Open access
  40. Pirashvili M., Pirashvili T. (2022) ‘Symmetric cohomology of groups and Poincaré duality’ Journal of Algebra 614, 177-198. DOI
  41. Pirashvili M. (2023) ‘Obstruction theories of extensions via track categories’ Journal of Algebra and its Applications. DOI
  42. Abdelmotaleb H., Wojtyś M., McNeile C. “A Comparison of a Novel Optimized GSDMM Model with K-Means Clustering For Topic Modelling Of Free Text”, Journal of Machine Intelligence and Data Science (JMIDS), DOI: 10.11159/jmids.2023.007