José F. Torres

José F. Torres

Ph.D. student

Citations and socials

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José F. Torres Maldonado received the Degree of Computer Science (2017) and a Master Degree of Computer Science from Pablo de Olavide University, Seville, Spain (2018). He is currently a Ph.D. student in Computer Science at Pablo de Olavide University, Seville, Spain and teaching assistant in two master degrees: “Análisis Bioinformático Avanzado”, by Pablo de Olavide University and “Máster Universitario en Inteligencia Artificial” by the Spanish Association for Artificial Intelligence (AEPIA). He is also teaches at Universidad Nacional de Educación a Distancia (UNED). His research focuses on Big Data, Time Series forecasting, Artificial Intelligence and Deep Learning techniques.

He’s the author of 6 articles in international conferences according to JCR (Q1 and Q2) and author of 5 articles in international conference. In addition, he has also been a reviewer in the IEEE International Conference on Data Science and Advanced Analytics (DSAA 2017), the Conference on Health Information Science (HIS 2017), the International Conference Soft Computing and Pattern Recognition (SoCPaR 2018) and the International Conference on Pattern Recognition Applications and Methods (ICPRAM 2019).

He is working as a researcher in Data Science & Big Data Lab. in the Area of Language and Computer Systems – Division of Computer Science at the Pablo de Olavide University where he has participated in four projects: “Big Data Streaming: Análisis de datos masivos continuos. Modelos predictivos.” and “Big Time-Aware Data: Análisis de datos masivos indexados en el tiempo”, both founded by the Spanish Ministry of Economy and Competitiveness, “CONBIDA: Construcción basada de big data: modelos predictivos para la transformación digital de procesos en la construcción”, co-founded by DETEA and “ANAMERLEC: Análisis de datos asociados a la predicción del mercado eléctrico”, co-founded by ISOTROL.

Teaching

Computer Science (Major: Information Systems), Pablo de Olavide University
  • Programming Fundamentals
  • Object-oriented Programming
  • Advanced Programming
  • Technology Integration (Coordinator)
  • Fundamentals of Information Systems (former)
  • Project engineering (former)
Computer Engineering, National University of Distance Education (UNED)
  • Database Systems
  • Operating Systems
  • Design and Administration of Operating Systems
  • Computer graphics
  • Databases
  • Fundamentals of Artificial Intelligence
  • Criminality and Computer Security (former)
Advanced Bioinformatics Analysis, Pablo de Olavide University
  • Data Science and Big Data
Artificial Intelligence, Menéndez Pelayo International University
  • Complex and Temporal Data

Projects

0313_PERSISTAH_5_P. Earthquake resilient schools in the region of Algarve and Huelva.

Principal Investigator: João M. C. Estêvão (Partner Pablo de Olavide University: Francisco Martínez Álvarez).
Funding: European Union (POCTEP).
2016-2020.

TIN2017-88209-C2-1-R. Big Data Streaming: Análisis de datos masivos continuos. Modelos predictivos.

Principal Investigator: Alicia Troncoso Lora, Francisco Martínez Álvarez
2018-2020

TIN2014-55894-C2-2-R. Big Time-Aware Data: Análisis de datos masivos indexados en el tiempo.

Principal Investigator: Alicia Troncoso Lora
2015-2018

Net LIoT: Diseño e implementación de red y plataforma Smart Lantia IoT

Principal Investigator: Francisco Martínez Álvarez
Industrial partner: Lantia IOT
2018-2020

CONBIDA. Modelos predictivos para la gestión colaborativa de estimaciones en procesos de relación con el cliente

Principal Investigator: Alicia Troncoso Lora
Industrial partner:  Detea
2018-2019

easyM2M. Nuevos protocolos de comunicación para la creación de Smart Cities

Principal Investigator: Francisco Martínez Álvarez
Industrial partner: Lantia IOT
2017-2019

ANAMERLEC. Análisis de datos asociados a la predicción del mercado eléctrico

Principal Investigator: Alicia Troncoso Lora
Industrial partner:  Isotrol
2017-2018

ITC-20161178. AQUASIG: Sistema inteligente de gestión del abastecimiento y consumo urbano de agua

Principal Investigator: Francisco Martínez Álvarez
Industrial partnerGeographica
2016-2018

ITC-20151078. Optimización de la conservación de la infraestructura ferroviaria para transporte urbano

Principal Investigator: Francisco Martínez Álvarez
Industrial partner:  ec2ce
2015-2017

Publications

2020

F. Divina and J. F. Torres and M. García-Torres and F. Martínez-Álvarez and A. Troncoso

Hybridizing deep learning and neuroevolution: Application to the Spanish short-term electric energy consumption forecasting Journal Article

Applied Sciences, 10 (16), pp. 5487, 2020.

Abstract | Links | BibTeX

F. Martínez-Álvarez and G. Asencio-Cortés and J. F. Torres and D. Gutiérrez-Avilés and L. Melgar-García and R. Pérez-Chacón and C. Rubio-Escudero and A. Troncoso and J. C. Riquelme

Coronavirus Optimization Algorithm: A bioinspired metaheuristic based on the COVID-19 propagation model Journal Article

Big Data, 8 (4), pp. 308-322, 2020.

Abstract | Links | BibTeX

2019

J. F. Torres and D. Gutiérrez-Avilés and A. Troncoso and F. Martínez-Álvarez

Random Hyper-Parameter Search-Based Deep Neural Network for Power Consumption Forecasting Conference

IWANN 15th International Work-Conference on Artificial Neural Networks, 11506 , Lecture Notes in Computer Science 2019.

Links | BibTeX

J. F. Torres and A. Troncoso and I. Koprinska and Z. Wang and F. Martínez-Álvarez

Big data solar power forecasting based on deep learning and multiple data sources Journal Article

Expert Systems, 36 , pp. id12394, 2019.

Links | BibTeX

2018

A. Galicia and J. F. Torres and F. Martínez-Álvarez and A. Troncoso

A novel Spark-based multi-step forecasting algorithm for big data time series Journal Article

Information Sciences, 467 , pp. 800-818, 2018.

Abstract | Links | BibTeX

J. F. Torres and A. Galicia and A. Troncoso and F. Martínez-Álvarez

A scalable approach based on deep learning for big data time series forecasting Journal Article

Integrated Computer-Aided Engineering, 25 (4), pp. 335-348, 2018.

Abstract | Links | BibTeX

J. F. Torres and A. Troncoso and I. Koprinska and Z. Wang and F. Martínez-Álvarez

Deep learning for big data time series forecasting applied to solar power Conference

SOCO 13th International Conference on Soft Computing Models in Industrial and Environmental Applications, Advances in Intelligent Systems and Computing 2018.

Links | BibTeX

F. Divina and A. Gilson and F. Goméz-Vela and M. García-Torres and J. F. Torres

Stacking ensemble learning for short-term electricity consumption forecasting Journal Article

Energies, 11 (4), pp. 949, 2018.

Abstract | Links | BibTeX

2017

J. F. Torres and A. Troncoso and F. Martínez-Álvarez

Deep Learning - Based Approach for Time Series Forecasting with Application to Electricity Load Conference

IWINAC International Work-Conference on the Interplay Between Natural and Artificial Computation, Lecture Notes in computer Science 2017.

Links | BibTeX

A. Galicia and J. F. Torres and F. Martínez-Álvarez and A. Troncoso

Scalable Forecasting Techniques Applied to Big Electricity Time Series Conference

IWANN International Work-Conference on Artificial Neural Networks, Lecture Notes in Computer Science 2017.

Links | BibTeX

2016

A. M. Fernández and J. F. Torres and A. Troncoso and F. Martínez-Álvarez

Automated Spark clusters deployment for Big Data with standalone applications integration Conference

CAEPIA Multiconferencia de la Asociación Española para la Inteligencia Artificial (TAMIDA VII Simposio de Teoría y Aplicaciones de Minería de Datos), Lecture Notes in Computer Science 2016.

Links | BibTeX