| Date | Course / Event |
|---|---|
| 05/2026 | Genomic Data Science specialization (currently enrolled), Coursera, Online Course 1: Introduction to Genomic Technologies Course 2: Python for Genomic Data Science |
| 8/2024 | TRAIL Summer workshop, Lisbon, Portugal |
| 10/2022 | AutoML Fall School, Freiburg University, Germany |
| 05/2022 | Comparing Genes, Proteins, and Genomes (Bioinformatics III), Coursera, Online |
| 05/2022 | Genome Sequencing (Bioinformatics II), Coursera, Online |
| 04/2022 | Finding Hidden Messages in DNA (Bioinformatics I), Coursera, Online |
| 03/2022 - 04/2022 | Deep Learning specialization, Coursera, Online |
| 10/2021 - 11/2021 | Machine Learning, Coursera, Online |
| 08/2021 | Stochastic optimization, University of Jyvaskyla, Finland |
| 08/2021 | Multicriteria Design Optimization, University of Jyvaskyla, Finland |
| 02/2021 - 06/2021 | Artificial Neural Networks and Deep Learning, KU Leuven, Belgium |
| 09/2020 - 01/2021 | Simulation: Theory and Applications, KU Leuven, Belgium |
| 02/2020 - 06/2020 | Optimization: Special topics, KU Leuven, Belgium |
| 09/2020 | (1) Essential tools in R, (2) Time series analysis, (3) Introduction to Machine Learning, FLAMES Summer School, Online |
Morales-Hernández, A., De Carlo, F., Paldino, G. M., Trivel, P., Vaccaro, A., Bontempi, G. (2026). "A direct classification approach for reliable wind ramp event forecasting under severe class imbalance." Electric Power Systems Research.
Guastella, D.A., Morales-Hernández, A., Cornelis, B., Bontempi, G. (2025). "Calibration of vehicular traffic simulation models by local optimization." Transportation.
Amini, S., Vannieuwenhuyse, I., & Morales-Hernandez, A. (2024). "Constrained bayesian optimization: A review." IEEE Access.
Morales-Hernández, A., Rojas Gonzalez, S., Van Nieuwenhuyse, I. et al. (2024). "Bayesian multi-objective optimization of process design parameters in constrained settings with noise: an engineering design application." Engineering with Computers. 40.
Morales-Hernández, A., Van Nieuwenhuyse, I., Rojas Gonzalez, S., Jordens, J., Witters, M., Van Doninck, B. (2023). "Multi-objective Optimization of Adhesive Bonding Process in Constrained and Noisy Settings." In: Dorronsoro, B., Chicano, F., Danoy, G., Talbi, EG. (eds) Optimization and Learning. OLA 2023. Communications in Computer and Information Science. 1824. Springer, Cham.
Morales-Hernández, A., Van Nieuwenhuyse, I. & Rojas Gonzalez, S. (2022). "A survey on multi-objective hyperparameter optimization algorithms for machine learning." Artificial Intelligence Review. 56.
Morales-Hernández, A., Van Nieuwenhuyse, I., Nápoles, G. (2022). "Multi-objective Hyperparameter Optimization with Performance Uncertainty." In: Dorronsoro, B., Pavone, M., Nakib, A., Talbi, EG. (eds) Optimization and Learning. OLA 2022. Communications in Computer and Information Science. 1684. Springer, Cham.
Jordens, J., Van Doninck, B., Satrio, N. R., Hernández, A. M., Couckuyt, I., Van Nieuwenhuyse, I., & Witters, M. (2022). "Optimization of plasma-assisted surface treatment for adhesive bonding via artificial intelligence." In 2nd International Conference on Industrial Applications of Adhesives 2022: Selected Contributions of IAA 2022 Proceedings in Engineering Mechanics. (pp. 47-64). Cham: Springer International Publishing.
Morales-Hernández, A., Nápoles, G., Jastrzebska, A., Salgueiro, Y., & Vanhoof, K. (2022). "Online learning of windmill time series using Long Short-term Cognitive Networks." Expert Systems with Applications. 205.
Jastrzebska, A., Hernández, A. M., Nápoles, G., Salgueiro, Y., & Vanhoof, K. (2022). "Measuring wind turbine health using fuzzy-concept-based drifting models." Renewable Energy. 190.
Morales-Hernández, A., Cabrera-Hernández, L., Martínez-Jiménez, Y., García-Lorenzo, M. M., & Casas-Cardoso, G. M. (2021). "New Diversity Measures Based on the Coverage and Similarity of the Classification." Computación y Sistemas. 25(3).
Cabrera-Hernández, L., Morales-Hernández, A., Meneses Gómez, M., Meneses Marcel, A., Casas Cardoso, G. M., García Lorenzo, M. M. (2021). "Diversity-based selection of learning algorithms: a bagging approach." Investigación Operacional. 42(4).
Morales-Hernández, A., Casas Cardoso, G. M., González Rodríguez, E. F. (2019). "Diagnosis of the hypertension risk in children applying neurofuzzy systems." Revista Cubana de Informática Médica. 11(1).
Cabrera Hernández, L., González Nápoles, G., Santos, L. R., Morales-Hernández, A., Casas Cardoso, G. M., García Lorenzo, M. M., Martínez Jiménez, Y. (2017). "Building multi-classifiers systems with Ant Colony Optimization." Investigación Operacional. 38(4).
Cabrera Hernández, L., Morales-Hernández, A., Casas Cardoso, G. M., Martínez Jiménez, Y. (2015). "Genetic Algorithms with diversity measures to build classifiers systems." Investigación Operacional. 36(3).
Talk at BRAIN - AI cafe / online workshop, Belgium
Tutorial at ECAI2025 - The Engineering School, University of Bologna, Bologna, Italy
Poster at SUMO User conference - German Aerospace Center (DLR), Berlin-Adlershof, Germany
Poster at Rencontres Francophones Transport Mobilite (RFTM2024) - Université Libre de Bruxelles (ULB), Brussels, Belgium
Talk at International Conference on Optimization and Learning (OLA2023), University of Málaga, Málaga, Spain
Poster at Flanders Make: CMVPT Conference on Machines, Vehicles and Production Technology, Gent, Belgium
Talk at Winter Simulation Conference (WSC2022), Marina Bay Sands Hotel, Singapore
Talk at Joint International Scientific Conferences on AI and Machine Learning (BNAIC/BeNeLearn2022), Lamot Conference and Heritage Centre, Mechelen, Belgium
Talk at International Conference on Optimization and Learning (OLA2022), Syracusa Faculty of Architecture, Syracusa, Sicilia, Italy
Poster at Flanders Make: CMVPT Conference on Machines, Vehicles and Production Technology, Gent, Belgium
Talk at Winter Simulation Conference (WSC2021), JW Marriott Phoenix Desert Ridge Resort & Spa, Phoenix, Arizona, US (virtual)