Calibration of vehicular traffic simulation models by local optimization
Guastella, D.A., Morales-Hernández, A., Cornelis, B., Bontempi, G. (2025). "Calibration of vehicular traffic simulation models by local optimization." Transportation.
CV
Education
- Ph.D in Business Economics and Computer Science Engineering, Hasselt University and Ghent University, Belgium (2023)
- M.S. in Computer Science, Central University of Las Villas, Cuba (2019)
- B.S. in Computer Science, Central University of Las Villas, Cuba (2014)
Work experience
- October 2023: Postdoctoral researcher
- Université Libre de Bruxelles
- March - September 2023: Ph.D. student
- Faculty of Engineering and Architecture, Ghent University, Belgium
- June - September 2023: Researcher as member of Flanders Make@UHasselt
- Hasselt University, Belgium
- December 2019 - September 2023: Ph.D. student and teaching assistant
- Hasselt University, Belgium
- October 2017 - November 2019: Teaching assistant
- Central University of Las Villas, Cuba
- September 2014 - September 2017: Senior Specialist in ICT
- Company of Information Technologies for Defense, Cuba
Skills
- Technical skills
- Programming Languages: Python, R, Java, Matlab
- Libraries/frameworks: PyTorch, scikit-learn, pandas, AutomL, PyMOO, etc
- Tools: Git, Linux, LaTeX, Microsoft Office, Arena, etc
- Analytical / Research Skills
- Machine Learning & Deep Learning
- Optimization techniques
- Time series analysis
- Data visualization & statistical analysis
- XAI
- Professional / Transferable Skills
- Project management
- Scientific writing & publications
- Collaboration in interdisciplinary teams
- Communication & presentation
- Problem-solving
Publications
Constrained Bayesian Optimization: a review
Amini, S., Vannieuwenhuyse, I., & Morales-Hernandez, A. (2024). "Constrained bayesian optimization: A review." IEEE Access.
Bayesian multi-objective optimization of process design parameters in constrained settings with noise: an engineering design applications
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.
Multi-objective optimization of adhesive bonding process in constrained and noisy settings
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.
A survey on multi-objective hyperparameter optimization algorithms for machine learning
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.
Multi-objective Hyperparameter Optimization with Performance Uncertainty.
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.
Optimization of Plasma-Assisted Surface Treatment for Adhesive Bonding via Artificial Intelligence.
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.
Online learning of windmill time series using Long Short-term Cognitive Networks
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.
Measuring wind turbine health using fuzzy-concept-based drifting models
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.
New Diversity Measures Based on the Coverage and Similarity of the Classification
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).
Diversity-based selection of learning algorithms: a bagging approach
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).
Diagnosis of the hypertension risk in children applying neurofuzzy systems
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).
Building multi-classifiers systems with Ant Colony Optimization
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).
Genetic Algorithms with diversity measures to build classifiers systems
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).
Talks
A Tutorial on Smart Process Optimization with Bayesian Optimization: Leveraging AI for Efficient Decision-Making
Tutorial at The Engineering School, University of Bologna, Bologna, Italy
Leveraging SUMO for Traffic Twins: Experiences in Urban Traffic Processing
Poster at SUMO User conference - German Aerospace Center (DLR), Berlin-Adlershof, Germany
Integration of simulation and machine learning to predict the traffic in the event of disruptions
Poster at Rencontres Francophones Transport Mobilite (RFTM2024) - Université Libre de Bruxelles (ULB), Brussels, Belgium
Multi-objective optimization of adhesive bonding process in constrained and noisy settings
Talk at International Conference on Optimization and Learning (OLA2023), University of Málaga, Málaga, Spain
Tree-structured Parzen Estimators With Uncertainty For Hyperparameter Optimization Of Machine Learning Algorithms
Talk at Winter Simulation Conference (WSC2022), Marina Bay Sands Hotel, Singapore
Encore Abstract: Online learning of windmill time series using Long Short-term Cognitive Networks
Talk at Joint International Scientific Conferences on AI and Machine Learning (BNAIC/BeNeLearn2022), Lamot Conference and Heritage Centre, Mechelen, Belgium
Multi-objective hyperparameter optimization with performance uncertainty
Talk at International Conference on Optimization and Learning (OLA2022), Syracusa Faculty of Architecture, Syracusa, Sicilia, Italy
Multi-objective simulation optimization of the adhesive bonding process of materials
Talk at Winter Simulation Conference (WSC2021), JW Marriott Phoenix Desert Ridge Resort & Spa, Phoenix, Arizona, US (virtual)