Juan Mario Haut is an associate professor in the Department of Computer and Communication Technology at the University of Extremadura. The topic of his research covers the efficient analysis of remotely sensed (RS) images collected from Earth’s surface Observation platforms through the design and implementation of novel machine (ML) and deep learning (DL) processing methods. Dr. Haut delves into the application of Big Data and High-performance Computing (HPC) strategies, such as parallelization and distribution over GPU devices and Cloud Computing platforms, combined with deep neural networks for large and complex RS dataset analysis, such as hyperspectral and multispectral images. Dr. Haut is an author and a co-author of more than 120 scientific publications, including more than 70 contributions to JCR journals and more than 50 contributions to congresses, both national (17) and international (36) of relevance such as IEEE IGARSS, IEEE WHISPERS, or IEEE CBMS, and 1 book chapter.
M.E. Paoletti is a professor in the Department of Computer and Communication Technology at the University Centre of Merida, University of Extremadura, and a researcher at the Hyperspectral Computing Laboratory (HyperComp). Her research focuses on the efficient processing of remote sensed hyperspectral images through the development of deep learning techniques combined with graphical processing. Dr. Paoletti is author and co-author of 117 scientific publications, including 70 contributions to JCR journals, 49 contributions to congresses, both national (16) and international (33) of relevance such as IEEE IGARSS, IEEE WHISPERS, or IEEE CBMS, and 1 book chapter. Her JCR contributions stand out in the fields of computation (e.g., Journal of Supercomputing), neural networks (e.g., IEEE TNNLS and Neurocomputing), and remote sensing (e.g., IEEE TGRS, IEEE GRSL, or IEEE GRSM), having 8 highly cited articles with 2 research fronts (InCites Essential Science Indicators of Clarivate).