This page lists scientific articles and datasets published by EDISS students as part of their EDISS studies. The articles are typically written following research works performed as part of a project course, the summer internship or thesis work.
Datasets
The datasets published by EDISS students as part of their EDISS studies are available from the EDISS community on Zenodo: https://zenodo.org/communities/ediss/records
Scientific articles
1. Raza, M., Prokopova, H., Huseynzade, S., Azimi, S., & Lafond, S. (2022). Towards Integrated Digital-Twins: An Application Framework for Autonomous Maritime Surface Vessel Development. Journal of Marine Science and Engineering, 10(10), Article 1469. https://doi.org/10.3390/jmse10101469
2. Raza, M., Prokopova, H., Huseynzade, S., Azimi, S., & Lafond, S. (2022). SimuShips – A High Resolution Simulation Dataset for Ship Detection with Precise Annotations. In OCEANS 2022, Hampton Roads (pp. 1-5). (Oceans). IEEE. https://doi.org/10.1109/OCEANS47191.2022.9977182
3. Haris, M. J., Upreti, A., Kurtaran, M., Ginter, F., Lafond, S., & Azimi, S. (2023). Identifying gender bias in blockbuster movies through the lens of machine learning. Humanities & Social Sciences Communications, 10(1), Article 94. https://doi.org/10.1057/s41599-023-01576-3
4. Kibria, M. R., Akbar, R. I., Nidadavolu, P., Havryliuk, O., Lafond, S., & Azimi, S. (2023). Predicting efficacy of drug-carrier nanoparticle designs for cancer treatment: a machine learning-based solution. Scientific Reports, 13(1), Article 547 . https://doi.org/10.1038/s41598-023-27729-7
5. Grolleman, J., van Engeland, N.C.A., Raza, M. et al. Environmental stiffness restores mechanical homeostasis in vimentin-depleted cells. Sci Rep 13, 18374 (2023). https://doi.org/10.1038/s41598-023-44835-8
6. K. Nakhleh, M Raza, et al., “SACPlanner: Real-World Collision Avoidance with a Soft Actor Critic Local Planner and Polar State Representations,” 2023 IEEE International Conference on Robotics and Automation (ICRA), London, United Kingdom, 2023, pp. 9464-9470, doi: 10.1109/ICRA48891.2023.10161129
7. Billah, M. M., Manandhar, P., Krishan, S., Cedillo, A., Rexha, H., Lafond, S., Benke, K. K., Azimi, S., & Arslan, J. (2024). Explainability in Deep Learning Segmentation Models for Breast Cancer by Analogy with Texture Analysis. In Medical Imaging with Deep Learning (MIDL 2024) (Proceedings of Machine Learning Research).. https://hal.science/hal-04562334
8. Phuong T. Nguyen, Juri Di Rocco, Claudio Di Sipio, Mudita Shakya, Davide Di Ruscio, and Massimiliano Di Penta. 2024. Automatic Categorization of GitHub Actions with Transformers and Few-shot Learning. In Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM ’24). Association for Computing Machinery, New York, NY, USA, 468–474. https://doi.org/10.1145/3674805.3690752
9. Saad Waseem, Aicha Moussaid, Ricardo Chavez Tapia, S M Zahid Hasan, Iván Porres Paltor, Sebastien Lafond. Dynamic Test Case Prioritization and Selection for Continuous Integration using Reinforcement Learning. 7th International Conference on Systems Engineering (CIIS 2024).
10. Md Saleh Ibtasham , Sarmad Bashir, Muhammad Abbas, Zulqarnain Haider, Mehrdad Saadatmand, Antonio Cicchetti. ReqRAG: Enhancing Software Release Management through Retrieval-Augmented LLMs: An Industrial Study (2025) Requirements Engineering: Foundation for Software Quality (REFSQ 2025)
11. Riccardo Rubei, Aicha Moussaid, Claudio Di Sipio, Davide Di Ruscio. Prompt engineering and its implications on the energy consumption of Large Language Models. 9th International Workshop on Green and Sustainable Software (GREENS’25), 2025.
12. Henok Birru, Antonio Cicchetti, Malvina Latifaj, “Supporting Automated Documentation Updates in Continuous Software Development with Large Language Models”, 20th International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE 2025, April 4-6, Porto, Portugal.