Elsevier

Neurocomputing

Volume 390, 21 May 2020, Pages 294-296
Neurocomputing

Editorial
Fast learning of neural networks with application to big data processes

https://doi.org/10.1016/j.neucom.2019.10.057Get rights and content

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Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The first author thanks the Instituto Politecnico Nacional, the Secretaria de Investigacion y Posgrado, the Comision de Operacion y Fomento de Actividades Academicas, and the Consejo Nacional de Ciencia y Tecnologia for their help in this research. The third editor acknowledges the support by the COMET-K2 Center of the Linz Center of Mechatronics (LCM) funded by the Austrian federal government and the federal state of Upper Austria.

Jose de Jesus Rubio is a full time professor of the Sección de Estudios de Posgrado e Investigación, ESIME Azcapotzalco, Instituto Politécnico Nacional. He has published over 127 international journal papers with 1747 cites from Scopus. He serves in the Editorial Board for the IEEE Transactions on Neural Networks and Learning Systems, Neural Computing and Applications, Journal of Intelligent & Fuzzy Systems, Mathematical Problems in Engineering, International Journal of Advanced Robotic

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Jose de Jesus Rubio is a full time professor of the Sección de Estudios de Posgrado e Investigación, ESIME Azcapotzalco, Instituto Politécnico Nacional. He has published over 127 international journal papers with 1747 cites from Scopus. He serves in the Editorial Board for the IEEE Transactions on Neural Networks and Learning Systems, Neural Computing and Applications, Journal of Intelligent & Fuzzy Systems, Mathematical Problems in Engineering, International Journal of Advanced Robotic Systems, IEEE Latin America Transactions, Evolving Systems, International Journal of Business Intelligence and Data Mining. He is a Guest Editor for Neurocomputing (2019), Applied Soft Computing (2019), Frontiers in Neurorobotics (2019), Journal of Computational and Applied Mathematics (2019), Journal of Supercomputing (2019), Computational Intelligence and Neuroscience (2015–2016). He has been the tutor of 4 Ph.D. students, 17 Ph.D. students, 41 M.S. students, 4 S. students, and 17 B.S. students.

Yongping Pan received the Ph.D. degree in control theory and control engineering from the School of Automation Science and Engineering, South China University of Technology, Guangzhou, China, in 2011. He was a Control Systems Engineer with the Santak Electronic Co., Ltd., US Eaton Inc., Shenzhen, China, and the US Light Engineering Co., Ltd., Guangzhou, from 2007 to 2008. From 2011 to 2013, he was a Research Fellow at the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. He became a Research Fellow with the Department of Biomedical Engineering, National University of Singapore, Singapore in 2013 and was promoted to be one of the two Senior Research Fellows of the department in 2016. His research interests include nonlinear and adaptive control, neural networks and machine learning, and their applications to compliant robotics, human-robot interaction, and neural rehabilitation. He has authored or co-authored more than 90 peer-reviewed academic papers, including over 60 high-quality journal papers. He has been invited as an Associate Editor of several reputable journals and has served as an Organizing Committee Member of two international conferences.

Edwin Lughofer received his Ph.D.-degree from the Johannes Kepler University Linz (JKU) in 2005. He is currently Key Researcher with the Fuzzy Logic Laboratorium Linz/Department of Knowledge-Based Mathematical Systems (JKU) in the Softwarepark Hagenberg. He has participated in several basic and applied research projects on European and national level, with a specific focus on topics of Industry 4.0 and FoF (Factories of the Future). He has published around 200 publications in the fields of evolving fuzzy systems, machine learning and vision, data stream mining, chemometrics, active learning, classification and clustering, fault detection and diagnosis, quality control and predictive maintenance, including 80 journals papers in SCI-expanded impact journals, a monograph on ’Evolving Fuzzy Systems’ (Springer) and an edited book on ’Learning in Non-stationary Environments’ (Springer). In sum, his publications received 4200 references achieving an h-index of 36. He is associate editor of the international journals Information Sciences, IEEE Transactions on Fuzzy Systems, Evolving Systems, Information Fusion, Soft Computing and Complex and Intelligent Systems, the general chair of the IEEE Conference on EAIS 2014 in Linz, the publication chair of IEEE EAIS 2015, 2016, 2017 and 2018, the program co-chair of the International Conference on Machine Learning and Applications (ICMLA) 2018, the tutorial chair of IEEE SSCI Conference 2018, the publication chair of the 3rd INNS Conference on Big Data and Deep Learning 2018, and the Area chair of the FUZZ-IEEE 2015 conference in Istanbul. He co-organized around 12 special issues and more than 20 special sessions in international journals and conferences. In 2006 he received the best paper award at the International Symposium on Evolving Fuzzy Systems, in 2013 the best paper award at the IFAC conference in Manufacturing Modeling, Management and Control (800 participants) and in 2016 the best paper award at the IEEE Intelligent Systems Conference.

Mu-Yen Chen received the Ph.D. degree in information management from National Chiao-Tung University, Taiwan, in 2006. He is a Professor of information management with the National Taichung University of Science and Technology, Taiwan. His current research interests include artificial intelligent, soft computing, bio-inspired computing, data mining, deep learning, context-awareness, machine learning, and financial engineering, with over 100 publications in these areas. He has co-edited 12 special issues in international journals, such as the Computers in Human Behavior, the Applied Soft Computing, the Soft Computing, Information Fusion, the Neurocomputing, the Journal of Medical and Biological Engineering, The Electronic Library, the Library High Tech. He has served as an Editor-in-Chief and an Associate Editor of international journals, such as the IEEE Access, Journal of Medical, and Biological Engineering, International Journal of Big Data and Analytics in Healthcare, the Journal of Information Processing Systems, the International Journal of Social and Humanistic Computing while he is an editorial board member on several SCI journals.

Jianbin Qiu received the B.Eng. and Ph.D. degrees in Mechanical and Electrical Engineering from the University of Science and Technology of China, Hefei, China. He also received the Ph.D. degree in Mechatronics Engineering from the City University of Hong Kong, Kowloon, Hong Kong. He has been with the School of Astronautics, Harbin Institute of Technology since 2009, where is currently a Full Professor. He was an Alexander von Humboldt Research Fellow at the Institute for Automatic Control and Complex Systems, University of Duisburg-Essen, Duisburg, Germany. His current research interests include intelligent and hybrid control systems, signal processing, robotics and their industrial applications. Prof. Qiu is a Senior Member of IEEE and serves as the chairman of the IEEE Industrial Electronics Society Harbin Chapter, China. He is an Associate Editor of IEEE Transactions on Cybernetics.

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