Prof. Gualberto Asencio Cortés, Ph.D. is a Computer Science Engineer (University of Seville, 2008), Master in Software Engineering and Technology (University of Seville, 2010), Ph.D. (University of Pablo de Olavide, 2013) and he has an Executive Master in Innovation (EOI, Spain, 2016). He is Associate Professor of Computer Science (Profesor Titular de Universidad), in the area of Languages and Information Systems at the University of Pablo de Olavide. He is the author of more than 28 publications in impact journals according to JCR (20 of them between Q1 and Q2) and author of more than 30 articles in international and national conferences, most of them published in LNCS and LNBI. He has participated in three projects of the National Plan and three more of the Andalusian Research Plan. He is an editor of PLOS ONE (IF: 2.806, Q1), a regular reviewer of journals indexed in JCR (PLOS ONE, Bioinformatics, Neurocomputing, Computer and Geosciences, etc.) and member of the program committee in numerous international conferences. He has participated in more than 12 technology transfer contracts between the university and the company, including ISOTROL, Red Eléctrica Española and DETEA. He has 5 months of international research stays and 3 national months.
The research lines of Prof. Gualberto Asencio Cortés, Ph.D. are focused on data mining, machine learning, prediction of time series and bioinformatics, with different fields of application: prediction of natural series (seismic, air quality, meteorological, agronomic, …), prediction of electricity consumption and market prices, prediction of urban traffic, as well as bioinformatics in prediction of biological structures. He has also been data scientist and member of the steering committee responsible for artificial intelligence and data science technologies at the private company easytosee AgTech SL for more than 2 years (2015-2017).
PHILNet: A Novel Efficient Approach for Time Series Forecasting using Deep Learning Journal Article
Information Sciences, in press , 2023.
From Simple to Complex: A Sequential Method for Enhancing Time Series Forecasting with Deep Learning Journal Article
Logic Journal of the IGPL, in press , 2023.
A bioinspired ensemble approach for multi-horizon reference evapotranspiration forecasting in Portugal Conference
8th ACM/SIGAPP Symposium on Applied Computing (SAC ’23), ACM 2023.
Embedded temporal feature selection for time series forecasting using deep learning Conference
DIAFAN-TL: An instance weighting-based transfer learning algorithm with application to phenology forecasting Journal Article
Knowledge-Based Systems, 254 , pp. 109644, 2022.
Olive Phenology Forecasting Using Information Fusion-Based Imbalanced Preprocessing and Automated Deep Learning Conference
13469 , Lecture Notes in Computer Science 2022.
Automatic Eligibility of Sellers in an Online Marketplace: A Case Study of Amazon Algorithm Journal Article
Information, 13 (44), pp. 1–16, 2022.
Earthquake Prediction in California using Feature Selection techniques Conference
16th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2021), Advances in Intelligent Systems and Computing 2022.
A new hybrid method for predicting univariate and multivariate time series based on pattern forecasting Journal Article
Information Sciences, 586 , pp. 611–627, 2022.
Streaming big time series forecasting based on nearest similar patterns with application to energy consumption Journal Article
Logic Journal of the IGPL, 31 (2), pp. 255-270, 2022.
Feature-Aware Drop Layer (FADL): A Nonparametric Neural Network Layer for Feature Selection Conference
SOCO 17th International Conference on Soft Computing Models in Industrial and Environmental Applications, 531 , Lecture Notes in Networks Systems 2022.
HLNet: A Novel Hierarchical Deep Neural Network for Time Series Forecasting Conference
SOCO International Conference on Soft Computing Models in Industrial and Environmental Applications, 1401 , Advances in Intelligent Systems and Computing 2021.
A Model-Based Deep Transfer Learning Algorithm for Phenology Forecasting Using Satellite Imagery Conference
HAIS, 12886 , Lecture Notes in Computer Science 2021.
Serial co-expression analysis of host factors from SARS-CoV viruses highly converges with former high-throughput screenings and proposes key regulators Journal Article
Briefings in Bioinformatics, 22 (2), pp. 1038–1052, 2021.
A New Forecasting Algorithm Based on Neighbors for Streaming Electricity Time Series Conference
HAIS 15th International Conference on Hybrid Artificial Intelligence Systems, Lecture Notes in Computer Science 2020.