Federico Divina obtained his Ph.D. in Artificial Intelligence from the Vrije Universiteit of Amsterdam, and after that he worked as a postdoc at the University of Tilburg, within the European project NEWTIES. In 2006 he moved to the Pablo de Olavide University, where he is actually an Associate Professor.
He has been working on knowledge extraction since his Ph.D. thesis at the Vrije Universiteit of Amsterdam. He has extensive experience in the application of Machine Learning, especially techniques based on Soft Computing, for the extraction of knowledge from massive data.
His main research interests are:
- Bioinformatics
- Evolutionary Computation
- Machine Learning
- Big Data
Projects
Federico Divina has participated in various research project projects, for instance:
- Differential: this project aims to develop new tools and methods to manage and analyse information coming from several sources with the final goal of better understanding how and when energy is consumed in distributed facilities. This project was developed as a coordinated project with three complementary research groups from three different universities (Universidad de Granada, Universidad Pablo de Olavide and Universidad de Castilla La Mancha).
- GALICIAME: project that aimed at applying machine learning tools in order to extract knowledge from genetic data related to spinal muscular atrophy (SMA), in collaboration with the “Centro Andaluz de Biología del Desarrollo” (CABD).
- NEWTIES: EU project that aimed at developing an artificial society. This project involved the Vrije Universiteit van Amsterm, the University of Tilburg, the Napier University, University of Surrey, Napier University and Eötvös Loránd University.
Publications
For a complete list of my publications, please visit my Google Scholar Profile or my ORCID.
2023 |
Neuroevolutionary Transfer Learning for Time Series Forecasting Conference SOCO International Conference on Soft Computing Models in Industrial and Environmental Applications, vol. 749, Lecture Notes in Networks and Systems 2023. |
Dataset of fundus images for the diagnosis of ocular toxoplasmosis Journal Article In: Data in Brief, pp. 109056, 2023. |
Evolutionary feature selection on high dimensional data using a search space reduction approach Journal Article In: Engineering Applications of Artificial Intelligence, vol. 117, pp. 105556, 2023. |
2022 |
Distribution level Electric current consumption and meteorological data set of the East region of Paraguay Journal Article In: Data in Brief, vol. 40, pp. 107699, 2022. |
Data of transcriptional effects of the merbarone-mediated inhibition of TOP2 Journal Article In: Data in Brief, vol. 44, pp. 108499, 2022. |
Analysis of Electric Energy Consumption Profiles Using a Machine Learning Approach: A Paraguayan Case Study Journal Article In: Electronics, vol. 11, no. 2, pp. 267, 2022. |
Explainable Artificial Intelligence for the Electric Vehicle Load Demand Forecasting Problem Conference SOCO 17th International Conference on Soft Computing Models in Industrial and Environmental Applications, Advances in Intelligent Systems and Computing 2022. |
2021 |
Scatter search for high-dimensional feature selection using feature grouping Conference GECCO Genetic and Evolutionary Computation Conference, 2021. |
A Trust-Based Methodology to Evaluate Deep Learning Models for Automatic Diagnosis of Ocular Toxoplasmosis from Fundus Images Journal Article In: Diagnostics, vol. 11, no. 11, pp. 1951, 2021. |
Genome-wide prediction of topoisomerase II $beta$ binding by architectural factors and chromatin accessibility Journal Article In: PLoS computational biology, vol. 17, no. 1, pp. e1007814, 2021. |
Adjacent Inputs With Different Labels and Hardness in Supervised Learning Journal Article In: IEEE Access, pp. 162487–162498, 2021. |
Technical analysis strategy optimization using a machine learning approach in stock market indices Journal Article In: Knowledge-Based Systems, pp. 107119, 2021. |
Advanced Optimization Methods and Big Data Applications in Energy Demand Forecast Journal Article In: Applied Sciences, vol. 11, no. 3, pp. 1261, 2021. |
A multi-GPU biclustering algorithm for binary datasets Journal Article In: Journal of Parallel and Distributed Computing, vol. 147, pp. 209–219, 2021. |
Forecasting Electricity Consumption Data from Paraguay Using a Machine Learning Approach Conference SOCO 16th International Conference on Soft Computing Models in Industrial and Environmental Applications, vol. 1401, Advances in Intelligent Systems and Computing 2021. |