Maryam Abbasi

maryam.abbasi@esg.ipsantarem.pt

https://www.cienciavitae.pt/4317-9113-7F7C

https://orcid.org/0000-0002-9011-0734

Researcher in the field of Artificial Intelligence applied to Bioinformatics, Health, and Data Sciences, with special focus on machine learning, generative models, multi-agent reinforcement learning, and biomedical data analysis. Experience in interdisciplinary projects that combine AI, computational biology, computational neuroscience, and education, in collaboration with national and international institutions. Engages in higher education teaching and actively participates in advanced training initiatives and scientific dissemination.

Research Interests

Artificial Intelligence; Machine Learning; Bioinformatics; AI for Health; Generative Models; Reinforcement Learning; Multi-Agent Systems; Computational Neuroscience; Data Analysis

Latest Publications

[2026] Abbasi, M., Brito-Costa, S., Teixeira, A. R., & Martins, P. (2026). Attention-based transfer learning for multimodal EEG and eye tracking in brain–computer interfaces. In H. Mori, Y. Asahi, D. D. Schmorrow, & C. M. Fidopiastis (Eds.), HCI International 2025 – Late breaking papers (Lecture Notes in Computer Science, Vol. 16333). Springer. https://doi.org/10.1007/978-3-032-12660-3_21

[2025] Oliveira, R. I., Pereira, T. O., Abbasi, M., Salvador, J. A. R., & Arrais, J. P. (2025). Deep learning for small-molecule drug discovery: From molecular design to clinical translation. Journal of Pharmaceutical Analysis. Advance online publication. https://doi.org/10.1016/j.jpha.2025.101533

[2025] Abbasi, M., Vasconcelos, V., Vicente, E. M. C. O. S., Santos, A. L. M., & Arrais, J. P. (2025). A novel deep learning framework for predicting antimicrobial peptide activity using ProtBert and neural networks. In N. Gonçalves, H. P. Oliveira, & J. A. Sánchez (Eds.), Pattern recognition and image analysis (Lecture Notes in Computer Science, Vol. 15938). Springer. https://doi.org/10.1007/978-3-031-99568-2_6

[2024] Abbasi, M., Carvalho, F. G., Ribeiro, B., & Arrais, J. P. (2024). Predicting drug activity against cancer through genomic profiles and SMILES. Artificial Intelligence in Medicine, 150, Article 102820. https://doi.org/10.1016/j.artmed.2024.102820

[2022] Abbasi, M., Santos, B. P., Pereira, T. C., Sofia, R., Monteiro, N. R. C., Simões, R. M. M., Ribeiro, B., Oliveira, J. L., & Arrais, J. P. (2022). Designing optimized drug candidates with generative adversarial networks. Journal of Cheminformatics, 14(1), Article 40. https://doi.org/10.1186/s13321-022-00623-6