Dr Benjamin Mora

Associate Professor

Computer Science

+44 (0) 1792 295575

b.mora@swansea.ac.uk

Office - 335
Third Floor
Computational Foundry
Bay Campus

Available For Postgraduate Supervision

Research Links

https://orcid.org/0000-0002-2945-3519

ResearcherID

About

Ben Mora is an Associate Professor in the department of Computer science, Swansea University.

Publications

Research Highlights

Tang, T., Mishra, A., Mora, B., Al-Sarireh, B., Irvine, O., Mauri, B., Higginbotham, V., Bandaranayake, P., Chandrashekhara, S., Kanamarlapudi, V., & Roy, D. (2026). High-efficacy and affordable hyperspectral pancreatic tissue image analysis using near-infrared spectroscopy. Journal of Pathology Informatics, 21, 100651
https://doi.org/10.1016/j.jpi.2026.100651, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa71658
Eshkiki, H., Tanhaei, F., Caraffini, F., & Mora, B. (2025). A Survey of the Application of Explainable Artificial Intelligence in Biomedical Informatics. Applied Sciences, 15(24), 12934
https://doi.org/10.3390/app152412934, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa71126
Tang, Z., Duckworth, E., Mora, B., Sarireh, B., Mortimer, M., & Roy, D. (2024). Advancing frontline early pancreatic cancer detection using within-class feature extraction in FTIR spectroscopy. Scientific Reports, 14(1), 28940
https://doi.org/10.1038/s41598-024-79153-0, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa68350
Major, L., Clare, A., Daykin, J., Mora, B., & Zarges, C. (2025). Heuristics for the run-length encoded Burrows–Wheeler transform alphabet ordering problem. Journal of Heuristics, 31(1), 11
https://doi.org/10.1007/s10732-025-09548-3, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67539
Duckworth, E., Hole, A., Deshmukh, A., Chaturvedi, P., Chilakapati, M., Mora, B., & Roy, D. (2022). Improving Vibrational Spectroscopy Prospects in Frontline Clinical Diagnosis: Fourier Transform Infrared on Buccal Mucosa Cancer. Analytical Chemistry, 94(40), 13642-13646.
https://doi.org/10.1021/acs.analchem.2c02496, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60963

All Research

Journal Articles

Tang, T., Mishra, A., Mora, B., Al-Sarireh, B., Irvine, O., Mauri, B., Higginbotham, V., Bandaranayake, P., Chandrashekhara, S., Kanamarlapudi, V., & Roy, D. (2026). High-efficacy and affordable hyperspectral pancreatic tissue image analysis using near-infrared spectroscopy. Journal of Pathology Informatics, 21, 100651
https://doi.org/10.1016/j.jpi.2026.100651, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa71658
Eshkiki, H., Tanhaei, F., Caraffini, F., & Mora, B. (2025). A Survey of the Application of Explainable Artificial Intelligence in Biomedical Informatics. Applied Sciences, 15(24), 12934
https://doi.org/10.3390/app152412934, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa71126
Major, L., Clare, A., Daykin, J., Mora, B., & Zarges, C. (2025). Heuristics for the run-length encoded Burrows–Wheeler transform alphabet ordering problem. Journal of Heuristics, 31(1), 11
https://doi.org/10.1007/s10732-025-09548-3, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa67539
Tang, Z., Duckworth, E., Mora, B., Sarireh, B., Mortimer, M., & Roy, D. (2024). Advancing frontline early pancreatic cancer detection using within-class feature extraction in FTIR spectroscopy. Scientific Reports, 14(1), 28940
https://doi.org/10.1038/s41598-024-79153-0, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa68350
Eshkiki, H., Mora, B., & Xie, X. (2024). Fully Connected Networks on a Diet With the Mediterranean Matrix Multiplication. IEEE Transactions on Neural Networks and Learning Systems, 35(1), 634-647.
https://doi.org/10.1109/tnnls.2022.3176197, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60038
Duckworth, E., Hole, A., Deshmukh, A., Chaturvedi, P., Chilakapati, M., Mora, B., & Roy, D. (2022). Improving Vibrational Spectroscopy Prospects in Frontline Clinical Diagnosis: Fourier Transform Infrared on Buccal Mucosa Cancer. Analytical Chemistry, 94(40), 13642-13646.
https://doi.org/10.1021/acs.analchem.2c02496, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60963
Nagoor, O., Whittle, J., Deng, J., Mora, B., & Jones, M. (2022). Sampling strategies for learning-based 3D medical image compression. Machine Learning with Applications, 8, 100273
https://doi.org/10.1016/j.mlwa.2022.100273, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59383
Doidge, I., Jones, M., & Mora, B. (2012). Mixing Monte Carlo and progressive rendering for improved global illumination. The Visual Computer, 28(6-8), 603-612.
https://doi.org/10.1007/s00371-012-0703-2, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa13561
Clarke, L., Chen, M., Mora, B., & Mora, B. (2011). Automatic Generation of 3D Caricatures Based on Artistic Deformation Styles. IEEE Transactions on Visualization and Computer Graphics, 17(6), 808-821.
https://doi.org/10.1109/TVCG.2010.76, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa7578
Mora, B. (2011). Naive ray-tracing. ACM Transactions on Graphics, 30(5), 1
https://doi.org/10.1145/2019627.2019636, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa8151
Mora, B. (2011). Naive ray-tracing: A divide-and-conquer approach. ACM Transactions on Graphics, 30(5), 117
https://doi.org/10.1145/2019627.2019636, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa7579
Mora, B., Maciejewski, R., Chen, M., Ebert, D., & Mora, B. (2009). Visualization and Computer Graphics on Isotropically Emissive Volumetric Displays. IEEE Transactions on Visualization and Computer Graphics, 15(2), 221
https://doi.org/10.1109/TVCG.2008.99, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa155
Aidong, L., Ebert, D., Qiao, W., Kraus, M., & Mora, B. (2007). Volume illustration using wang cubes. ACM Transactions on Graphics, 26(2), 11
https://doi.org/10.1145/1243980.1243985, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa1691
Mora, B. & Ebert, D. (2005). Low-complexity maximum intensity projection. ACM Transactions on Graphics, 24(4), 1392
https://doi.org/10.1145/1095878.1095886, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa1690
Mora, B. & Evert, D. (2004). Instant Volumetric Understanding with Order-Independent Volume Rendering. Computer Graphics Forum, 23(3), 489
https://doi.org/10.1111/j.1467-8659.2004.00780.x, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa1692

Book Chapters

Tsitiridis, A., Mora, B., Richardson, M., & Mora, B. (2013). Hierarchical Object Recognition Model of Increased Invariance. Engineering Applications of Neural Networks -202).
https://doi.org/10.1007/978-3-642-41013-0_20, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa21546

Conference Contributions

Kapcia, M., Eshkiki, H., Duell, J., Fan, X., Zhou, S., & Mora, B. (2021). ExMed: An AI Tool for Experimenting Explainable AI Techniques on Medical Data Analytics. In 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI) (pp. 841-845). IEEE.
https://doi.org/10.1109/ictai52525.2021.00134, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58534
Nagoor, O., Whittle, J., Deng, J., Mora, B., Jones, M., & Whittle, J. (2021). MedZip: 3D Medical Images Lossless Compressor Using Recurrent Neural Network (LSTM). In 2020 25th International Conference on Pattern Recognition (ICPR)IEEE.
https://doi.org/10.1109/icpr48806.2021.9413341, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55395
http://dx.doi.org/10.1109/icpr48806.2021.9413341
Nagoor, O., Whittle, J., Deng, J., Mora, B., & Jones, M. (2020). Lossless Compression For Volumetric Medical Images Using Deep Neural Network With Local Sampling. In 2020 IEEE International Conference on Image Processing (ICIP) (pp. 2815-2819). IEEE.
https://doi.org/10.1109/icip40778.2020.9191031, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55355
Major, L., Clare, A., Daykin, J., Mora, B., Gamboa, L., & Zarges, C. (2020). Evaluation of a Permutation-Based Evolutionary Framework for Lyndon Factorizations. In Parallel Problem Solving from Nature – PPSN XVI (pp. 390-403). Springer International Publishing.
https://doi.org/10.1007/978-3-030-58112-1_27, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa54801
Ryan, A. & Mora, B. (2014). Variations on Image Reconstruction:Weighted Back Projection and Fourier Expectation Maximization. In Rita Borgo and Wen Tang (Ed.), Computer Graphics and Visual ComputingThe Eurographics Association.
https://doi.org/10.2312/cgvc.20141201, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa21545
https://diglib.eg.org/handle/10.2312/cgvc.20141201.009-016
Kammaje, R. & Mora, B. (2008). Row tracing using hierarchical occlusion maps. (pp. 27IEEE.
https://doi.org/10.1109/RT.2008.4634617, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa76
Barthe, L., Mora, B., Dodgson, N., Sabin, M., & Mora, B. (2002). Triquadratic reconstruction for interactive modelling of potential fields. (pp. 145
https://doi.org/10.1109/SMI.2002.1003539, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa1693

Supervision

Early Pancreatic Cancer Detection using Medical Imaging«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /» and Spectroscopy (current)

PhD

Other supervisor: Dr Deb Roy
New Algorithms For Machine Learning And Explainable Artificial Intelligence (awarded 2023)

PhD

Other supervisor: Prof Xianghua Xie
Personalised Learning Recommendation System for Programming Skills Development (current)

MSc

Other supervisor: Dr Cheng Cheng
Automated Micronucleus Detection in Cell Painting Images Using Machine Learning and Artificial Intelligence (current)

MSc

Other supervisor: Miss Claire Barnes
Original: Deep generative modelling for protein-ligand design: integrating Boltz-1 with reinforcement learning optimisation Amended: Integrating Boltz-1 with Direct Preference Optimisation for Protein–Ligand Design (current)

MSc

Other supervisor: Dr Joe Macinnes

Dr Benjamin Mora

Telephone number

Email address

Research Links

About

Publications

Research Highlights

All Research

Journal Articles

Book Chapters

Conference Contributions

Supervision

Early Pancreatic Cancer Detection using Medical Imaging«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /»«br /» and Spectroscopy (current)

New Algorithms For Machine Learning And Explainable Artificial Intelligence (awarded 2023)

Personalised Learning Recommendation System for Programming Skills Development (current)

Automated Micronucleus Detection in Cell Painting Images Using Machine Learning and Artificial Intelligence (current)

Original: Deep generative modelling for protein-ligand design: integrating Boltz-1 with reinforcement learning optimisation Amended: Integrating Boltz-1 with Direct Preference Optimisation for Protein–Ligand Design (current)