Prof. David Gutiérrez Avilés, Ph.D. is a Computer Science Engineer (University of Seville, 2010), Master in Software Engineering and Technology (University of Seville, 2013), Ph.D. (University of Seville, 2015). He is Assistant Professor in the area of Languages and Information Systems of University of Pablo de Olavide.
His main scientific achievement is the TrLab methodology to mining and evaluating of behavior patterns from large time-dependent datasets. This novel method extracts patterns from 3D large data using triclustering and genetic algorithms techniques. Through this research, several research productions and goals have been obtained: five JCR papers published, six conferences, a stay abroad in the University of Chile, belongings to one R&D team, a Regional project, and a National project; His Ph.D. thesis and intellectual property for the TrLab application.
The research lines of Prof. David Gutiérrez Avilés, Ph.D. are focused on: Electricity fraud detection in Big Data environments, On-line machine learning from Big data streaming, Analysis of Internet of Things protocols and sensor data analysis. Through this research, several research productions and goals have been obtained: 2 conference papers (in revision); belongings to an R&D team, a European project, a National projects, and 4 Business projects.
A new big data triclustering approach for extracting three-dimensional patterns in precision agriculture Journal Article
Neurocomputing, in press , 2021.
Discovering three-dimensional patterns in real-time from data streams: An online triclustering approach Journal Article
Information Sciences, in press , 2021.
SOCO 15th International Conference on Soft Computing Models in Industrial and Environmental Applications, Advances in Intelligent Systems and Computing 2020.
Big Data, 8 (4), pp. 308-322, 2020.
Big Data Research, 19-20 , pp. 100135, 2020.
SAC 35th Annual ACM Symposium on Applied Computing, 2020.
IWANN 15th International Work-Conference on Artificial Neural Networks, 11506 , Lecture Notes in Computer Science 2019.
SOCO 14th International Conference on Soft Computing Models in Industrial and Environmental Applications, Advances in Intelligent Systems and Computing 2019.
TRIQ: a new method to evaluate triclusters Journal Article
BioData Mining, 11 (1), pp. 15, 2018.
HAIS 13th International Conference on Hybrid Artificial Intelligence Systems, Lecture Notes in Computer Science 2018.
Hybrid Artificial Intelligent Systems: 11th International Conference, HAIS 2016, Seville, Spain, April 18-20, 2016, Proceedings, Lecture Notes in Computer Science 2016.
Evolutionary Bioinformatics, 11 , pp. 121—135, 2015.
Entropy, 17 (7), pp. 5000-5021, 2015.
The Scientific World Journal, 2014 , pp. 1-16, 2014.
LSL: A new measure to evaluate triclusters Conference
2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2014.