Alberto Fernández received the M.Sc. and Ph.D. degrees in computer science from the University of Granada, Granada, Spain, in 2005 and 2010, respectively. He is currently an Assistant Professor with the Department of Computer Science and Artificial Intelligence, University of Granada, Spain.

He has published more than 100 papers in highly rated JCR journals and international conferences. In 2013, 2014, and 2017 Dr. Fernández received the University of Granada Prize for Scientific Excellence Works in the field of Engineering. He has also been awarded in 2011 with the Lofti A. Zadeh Best Paper prize (IFSA Assocaiation). He has been recently selected as a Highly Cited Researcher http://highlycited.com  (in the field of Computer Science, 2017 Clarivate Analytics).

His research interests include classification in imbalanced domains, fuzzy rule learning, evolutionary algorithnms, multiclassification problems with ensembles and decompositions techniques, and data science in big data applications.

• V López, A Fernández, S García, V Palade, F Herrera An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics.  Information Sciences 250, 113-141, 2013
• M Galar, A Fernández, E Barrenechea, F Herrera. EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling. Pattern Recognition 46 (12), 3460-3471, 2013
• A Fernández, V López, M Galar, M José del Jesus, F Herrera. Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches.Knowledge-Based Systems, 2013
• A Fernández, S del Río, V López, A Bawakid, MJ del Jesus, JM Benítez, F Herrera. Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks.Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 4 -5, 2014
• S Ramírez-Gallego, A Fernández, S García, M Chen, F Herrera. Big Data: Tutorial and guidelines on information and process fusion for analytics algorithms with MapReduce. Information Fusion 42, 51-61, 2018

• Tutorial on Big Data with Fuzzy Logic. FUZZ-IEEE 2017 Naples.
• Special Session on Fuzzy Models for Data Science and Big Data. FUZZ-IEEE 2017 Naples.
  
• Tutorial on Big Data with Computational Intelligence. WCCI 2018 Rio de Janeiro.
• Special Session on Fuzzy Models for Data Science and Big Data. WCCI 2018 Rio de Janeiro.
• Special Session on Fuzzy Systems for Data Mining: data wrangling, machine learning, and real-world applications. WCCI 2018 Rio de Janeiro.