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Daniel Molina

Professor of Artificial Intelligence

University of Granada (UGR)

Biography

Daniel Molina is a professor of artificial intelligence at the University of Granada. His research interests include numerical optimization, evolutionary algorithms, deep learning, and machine learning.

Interests

  • Memetic algorithms
  • Artificial Intelligence
  • Deep Learning
  • Neuroevolution

Education

  • PhD in Artificial Intelligence, 2007

    University of Granada

  • BSc in Computer Science, 2000

    University of Granada (UGR)

Skills

Linux

100%

Python

100%

Java

100%

Experience

 
 
 
 
 

Teacher assistant

University of Granada (UGR)

Oct 1010 – Present Granada, Spain
Assistant teacher at the University of Granada.
 
 
 
 
 

Teacher assistant

University of Cadiz (UCA)

Feb 13130 – Jan 1010 Cádiz, Spain
Assistant teacher at the University of Cadiz.

Recent Publications

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NATURE- AND BIO-INSPIRED OPTIMIZATION: THE GOOD, THE BAD, THE UGLY AND THE HOPEFUL

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Ordering Artificial Intelligence Based Recommendations to Tackle the SDGs with a Decision-Making Model Based on Surveys

Sergio Alonso, Rosana Montes, Daniel Molina, Iván Palomares, Eugenio Martínez-Cámara, Manuel Chiachio, Juan Chiachio, Francisco J. Melero, Pablo García-Moral, Bárbara Fernández, Cristina Moral, Rosario Marchena, Javier Pérez de Vargas, Francisco Herrera
DOI URL

Lights and shadows in Evolutionary Deep Learning: Taxonomy, critical methodological analysis, cases of study, learned lessons, recommendations and challenges

A.D. Martinez, J. Del Ser, E. Villar-Rodriguez, E. Osaba, J. Poyatos, S. Tabik, D. Molina, F. Herrera

Performance analysis of real-coded evolutionary algorithms under a computationally expensive optimization scenario: 3D–2D Comparative Radiography

Oscar Gómez, Oscar Ibáñez, Andrea Valsecchi, Enrique Bermejo, Daniel Molina, Oscar Cordón
DOI URL

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if harnessed appropriately, may deliver the …
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Featured Publications

A.D. Martinez, J. Del Ser, E. Villar-Rodriguez, E. Osaba, J. Poyatos, S. Tabik, D. Molina, F. Herrera
January 2021 Information Fusion

Lights and shadows in Evolutionary Deep Learning: Taxonomy, critical methodological analysis, cases of study, learned lessons, recommendations and challenges

J. Del Ser, E. Osaba, D. Molina, X.-S. Yang, S. Salcedo-Sanz, D. Camacho, S. Das, P.N. Suganthan, C.A. Coello Coello, F. Herrera
January 2019 Swarm and Evolutionary Computation

Bio-inspired computation: Where we stand and what's next

PDF DOI
D. Molina, A. LaTorre, F. Herrera
January 2018 Cognitive Computation

An Insight into Bio-inspired and Evolutionary Algorithms for Global Optimization: Review, Analysis, and Lessons Learnt over a Decade of Competitions

PDF DOI

Recent Posts

Un nuevo inicio

Sé que tengo el blog muy parado, y creo saber por qué. El motivo es el idioma. No es que no sepa inglés, la verdad es que lo domino …
Last updated on Jun 28, 2022 1 min read blog, spanish

How to check the possible parameters for a function in Julia

Sometimes I create functions that receive a function as parameter, but in Julia the type is Function without any information, so when …
Last updated on May 8, 2022 2 min read programming, opensource

My Julia journey

In this post I am going to tell my Julia journey. I have read about Julia but not actually use it before version 0.7 just before 1.0. I …
Last updated on Mar 17, 2022 2 min read teaching, programming

My first Julia Package

For online teaching I use Moodle. I have a lot of experience using it (for more than 10 years). Unfortunately, the software could be …
Last updated on Mar 17, 2022 3 min read teaching, programming

About online teaching

These days we have to be enclosed in our houses by the coronavirus (COVID-19), so in my University (in Granada) as the others in Spain, …
Last updated on Mar 17, 2022 2 min read teaching, programming
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