Jordi Casas-Roma

Jordi Casas-Roma

Lecturer in the Computer Science Department at the UAB and Associate Researcher at the CVC

Publications

You can also find my articles on my Google Scholar profile.

Journal papers (indexed in ISI-JCR)

  1. Martínez, F. S., Casas-Roma, J., Subirats, L., & Parada, R. (2025). Energy‐Aware Regression in Spiking Neural Networks for Autonomous Driving: A Comparative Study With Convolutional Networks. International Journal of Intelligent Systems, 2025(1). https://doi.org/10.1155/int/4879993

  2. Lozano-Bagén, T., Martinez-Heras, E., Pontillo, G., Solana, E., Vivó, F., Petracca, M., Calvi, A., Garrido-Romero, S., Solé-Ribalta, A., Llufriu, S., Prados, F. and Casas-Roma, J. (2025) Evaluating topological and graph-theoretical approaches to extract complex multimodal brain connectivity patterns in multiple sclerosis. Health Information Science and Systems, Vol. 13, N. 68. https://doi.org/10.1007/s13755-025-00386-y

  3. F. S. Martínez, J. Casas-Roma, L. Subirats and R. Parada. (2025) Eco-Efficient Deployment of Spiking Neural Networks on Low-Cost Edge Hardware, in IEEE Networking Letters, In press, https://doi.org/10.1109/LNET.2025.3611426

  4. F. S. Martínez, J. Casas-Roma, L. Subirats, R. Parada (2024). Spiking neural networks for autonomous driving: A review. Engineering Applications of Artificial Intelligence, Volume 138, Part B, https://doi.org/10.1016/j.engappai.2024.109415

  5. M. Abad, J. Casas-Roma, F. Prados (2024). Generalizable disease detection using model ensemble on chest X-ray images. Scientific Reports Vol. 14, Art. N:5890. https://www.nature.com/articles/s41598-024-56171-6

  6. M. Lacasa, P. Launois, F. Prados, J. Alegre, J. Casas-Roma (2023). Unsupervised cluster analysis reveals distinct subtypes of ME/CFS patients based on peak oxygen consumption and SF-36 scores. Clinical Therapeutics, V. 45(12) pp. 1228-1235. https://doi.org/10.1016/j.clinthera.2023.09.007

  7. M. Lacasa, F. Prados, J. Alegre, J. Casas-Roma (2023). A synthetic data generation system for myalgic encephalomyelitis/chronic fatigue syndrome questionnaires. Scientific Reports 13, 14256. https://doi.org/10.1038/s41598-023-40364-6

  8. F. Sevilla Martínez, R. Parada, J. Casas-Roma (2023). CO2 impact on convolutional network model training for autonomous driving through behavioral cloning. Advanced Engineering Informatics Vol. 56. https://doi.org/10.1016/j.aei.2023.101968

  9. J. Casas-Roma, E. Martinez-Heras, A. Solé-Ribalta, E. Solana, E. Lopez-Soley, F. Vivó, M. Diaz-Hurtado, S. Alba-Arbalat, M. Sepulveda, Y. Blanco, A. Saiz, J. Borge-Holthoefer, S. Llufriu, F. Prados (2022). Applying multilayer analysis to morphological, structural and functional brain networks to identify relevant dysfunction patterns. Network Neuroscience 1-42. https://doi.org/10.1162/netn_a_00258

  10. Diaz-Hurtado, M., Martínez-Heras, E., Solana, E., Casas-Roma, J., Llufriu, S., Kanber, B., Prados, F. (2022). Recent advances in the longitudinal segmentation of multiple sclerosis lesions on magnetic resonance imaging: a review. Neuroradiology. http://doi.org/10.1007/s00234-022-03019-3

  11. E. Solana, E. Martinez-Heras, J. Casas-Roma, L. Calvet, E. Lopez-Soley, M. Sepulveda, N. Sola-Valls, C. Montejo, Y. Blanco, I. Pulido-Valdeolivas, M. Andorra, A. Saiz, F. Prados, S. Llufriu. (2019). Modified connectivity of vulnerable brain nodes in multiple sclerosis, their impact on cognition and their discriminative value. Scientific Reports 9, 20172. https://doi.org/10.1038/s41598-019-56806-z

  12. J. Casas-Roma. (2020). DUEF-GA: Data Utility and Privacy Evaluation Framework for Graph Anonymization. International Journal of Information Security (IJIS), Vol 19, pp. 465-478. https://doi.org/10.1007/s10207-019-00469-4
  13. J. Casas-Roma. (2019). An evaluation of vertex and edge modification techniques for privacy-preserving on graphs. Journal of Ambient Intelligence and Humanized Computing, Vol. 14, pp. 15109–15125. https://doi.org/10.1007/s12652-019-01363-6

  14. R. Parada, J. Font and J. Casas-Roma. (2019). Predicting Energy Generation Using Forecasting Techniques in Catalan Reservoirs. Energies (Special Issue Artificial Intelligence in Data Science For Energy Management in Sustainability), Vol 12(10), 1832. https://doi.org/10.3390/en12101832

  15. J. Casas-Roma, J. Salas, F. D. Malliaros and M. Vazirgiannis. (2019). k-Degree Anonymity on Directed Networks. Knowledge and Information Systems (KAIS), Vol. 61, pp. 1743-1768. https://doi.org/10.1007/s10115-018-1251-5
  16. M. Ros-Martín, J. Salas and J. Casas-Roma. (2018). Scalable non-deterministic clustering-based k-anonymization for rich networks. International Journal of Information Security (IJIS), Vol 18(2), pp. 219-238. http://doi.org/10.1007/s10207-018-0409-1

  17. F. Rousseau, J. Casas-Roma and M. Vazirgiannis. (2017). Community-Preserving Anonymization of Graphs. Knowledge and Information Systems (KAIS), Vol. 54(2), pp. 315-343. http://doi.org/10.1007/s10115-017-1064-y

  18. J. Casas-Roma, J. Herrera-joancomartí and V. Torra. (2016). A survey of graph-modication techniques for privacy-preserving on networks. Artificial Intelligence Review (AIRE), Vol 47(3), pp. 341-366. http://doi.org/10.1007/s10462-016-9484-8

  19. J. Casas-Roma, J. Herrera-joancomartí and V. Torra. (2016). k-Degree Anonymity And Edge Selection: Improving Data Utility In Large Networks. Knowledge and Information Systems (KAIS), Vol. 50(2), pp. 447-474. http://doi.org/10.1007/s10115-016-0947-7
  20. J. Casas-Roma, J. Herrera-joancomartí and V. Torra. (2015). Anonymizing Graphs: Measuring Quality for Clustering. Knowledge and Information Systems (KAIS), Vol. 44(3), pp. 507–528. http://doi.org/10.1007/s10115-014-0774-7

Conferences and workshops

  1. Casas-Roma, J., Lozano-Bagén, T. (2026). Comparing Graph Neural Networks for Single and Multi-layer Brain Connectivity Analysis in Multiple Sclerosis. In: Torra, V., Narukawa, Y., Domingo-Ferrer, J. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2025. Lecture Notes in Computer Science(), vol 15957. Springer, Cham. https://doi.org/10.1007/978-3-032-00891-6_27
  2. Subirà-Cribillers, M., Solé-Casaramona, J., Lladós, J., Casas-Roma, J. (2025). Graph Neural Networks for Multimodal Brain Connectivity Analysis in Multiple Sclerosis. In: Graph-Based Representations in Pattern Recognition. GbRPR 2025. Lecture Notes in Computer Science, vol 15727. Springer, Cham. https://doi.org/10.1007/978-3-031-94139-9_9

  3. M. Abad, J. Casas-Roma, F. Prados. (2022) Reducing the Learning Domain by Using Image Processing to Diagnose COVID-19 from X-Ray Image. In: Volume 356: Artificial Intelligence Research and Development, Frontiers in Artificial Intelligence and Applications, pp. 229-238. https://www.doi.org/10.3233/FAIA220343

  4. Parada R., Font J., Casas-Roma J. (2019) Forecasting Water Levels of Catalan Reservoirs. In: Torra V., Narukawa Y., Pasi G., Viviani M. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2019. Lecture Notes in Computer Science, Vol. 11676, pp. 164-176. Springer, Cham. https://doi.org/10.1007/978-3-030-26773-5_15

  5. Carrere-Molina, J., Subirats, L., Casas-Roma, J. (2019). Towards an analysis of post-transcriptional gene regulation in psoriasis via microRNAs using Machine Learning algorithms. 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS), pp. 600-603. Cordoba, Spain. https://doi.org/10.1109/CBMS.2019.00125

  6. Carmona, F., Conesa, J., Casas-Roma, J. (2019). Towards the Analysis of How Anonymization Affects Usefulness of Health Data in the Context of Machine Learning. 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS), pp. 604-608. Cordoba, Spain. https://doi.org/10.1109/CBMS.2019.00126

  7. J. Casas-Roma (2018). Data Utility Evaluation Framework for Graph Anonymization. Actas de la XV Reunión Española sobre Criptología y Seguridad de la Información (RECSI), pp. 123-128. Granada, Spain. ISBN: 978-84-09-02463-6

  8. I. Guitart, J. Conesa, J. Casas-Roma (2016). A Preliminary Study about the Analytic Maturity of Educational Organizations. Proceedings of the 2016 International Conference on Intelligent Networking and Collaborative Systems (INCoS), pp. 345-350. IEEE. https://doi.org/10.1109/INCoS.2016.53

  9. J. Casas-Roma (2015). An Evaluation of Edge Modification Techniques for Privacy-Preserving on Graphs. Proceedings of the 12th International Conference on Modeling Decisions for Artificial Intelligence, volume 9321 of Lecture Notes in Computer Science, pp. 180-191. Springer International Publishing. http://doi.org/10.1007/978-3-319-23240-9_15

  10. J. Casas-Roma, F. Rousseau (2015). Community-preserving generalization of social networks. Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM ’15), pp. 1465-1472, ACM. http://doi.org/10.1145/2808797.2808854

  11. J. Casas-Roma (2014). Privacy-Preserving on Graphs using Randomization and Edge-Relevance. In V. Torra, Y. Narukawa and Y. Endo, editors, Proceedings of the 11th International Conference on Modeling Decisions for Articial Intelligence, volume 8825 of Lecture Notes in Articial Intelligence, pp. 204-216. Berlin, Heidelberg, 2014. Springer Berlin Heidelberg. http://doi.org/10.1007/978-3-319-12054-6_18

  12. Casado, C.; Casas-Roma, J.; Córcoles, C. P.; Minguillón, J.; Peña, I. (2014). Analyzing Learner’s Participation in a WordPress-based Personal Teaching Environment. In: The Personal Learning Environments Conference. Tallinn, 2014.

  13. Casas-Roma, J., Herrera-joancomartí, J., and Torra, V. (2013). Analyzing the Impact of Edge Modifications on Networks. In The 10th International Conference on Modeling Decisions for Artificial Intelligence (pp. 296-307). Barcelona: Springer-Verlag. http://doi.org/10.1007/978-3-642-41550-0_26
  14. Casas-Roma, J., Herrera-Joancomartí, J., and Torra, V. (2013). An Algorithm For k-Degree Anonymity On Large Networks. In The 2013 IEEE/ACM International Conference on Advances on Social Networks Analysis and Mining (pp. 671-675). Niagara Falls, http://doi.org/10.1145/2492517.2492643
  15. Casas-Roma, J., Herrera-Joancomartí, J., and Torra, V. (2012). Comparing Random-based and k-Anonymity-based Algorithms for Graph Anonymization. In The 9th International Conference on Modeling Decisions for Artificial Intelligence (pp. 197-209). Girona, http://doi.org/10.1007/978-3-642-34620-0_19
  16. Casas-Roma, J., Herrera-Joancomartí, J., and Torra, V. (2012). Algoritmos genéticos para la anonimización de grafos. In XII Reunión Española sobre Criptología y Seguridad de la Información (RECSI 2012) (pp. 243-248). Donostia-San Sebastián.

Book chapters

  1. J. Casas-Roma, J. Herrera-joancomartí and V. Torra. (2015) A Summary of k-Degree Anonymous Methods for Privacy-Preserving on Networks. In G. Navarro-Arribas and V. Torra, editors, Advanced Research in Data Privacy, volume 567 of Studies in Computational Intelligence, pp. 231-249. Berlin, Heidelberg. Springer Berlin Heidelberg. http://doi.org/10.1007/978-3-319-09885-2_13

Scientific papers and reports

  1. Casas-Roma, J., Herrera-Joancomartí, J., and Torra, V. (2014). Privacy-preserving and data utility in graph mining. Universitat Autònoma de Barcelona (UAB). Available at http://hdl.handle.net/10803/285566.

  2. Casas-Roma, J., Herrera-Joancomartí, J., and Torra, V. (2013). Evolutionary Algorithm for Graph Anonymization, Available at http://arxiv.org/abs/1310.0229v2

  3. Casas-Roma, J. (2011). Preservación de la privacidad en procesos de minería de datos basados en grafos. Universidad Nacional de Educación a Distancia (UNED). Available at https://hdl.handle.net/20.500.14468/14508.