Juan M. Haut
Dept. Computer and Communication Technology, University of Extremadura, Spain.
Tenured Associate Professor
(Profesor Titular de Universidad)
Juan M. Haut is a Tenured Associate Professor (Profesor Titular de Universidad) at the University of Extremadura in Cáceres, Spain, and a member of the Hyperspectral Computing Laboratory (HyperComp) in the Department of Computer and Communication Technology. He received his Ph.D. in Information Technology from the same university in 2019, with international mention.
His research develops deep learning methods for hyperspectral remote sensing, combining GPU acceleration, high-performance computing and distributed systems for efficient analysis of large-scale data. Recent work covers band selection, semantic segmentation, spectral unmixing and image retrieval, with applications extending to network intrusion detection. His publication list includes 95 journal articles and 63 conference contributions; Google Scholar provides current citation metrics.
An IEEE Senior Member, he chairs the Spanish Chapter of the IEEE Geoscience and Remote Sensing Society (GRSS) and serves as an Associate Editor of Remote Sensing and an Editorial Board Member of Scientific Reports. He has led competitive research projects supported by the European Commission, Spain’s Agencia Estatal de Investigación and the BBVA Foundation’s Leonardo Grants programme. In 2022, he received the University of Extremadura’s Research Excellence Award for young researchers in the technical field. Further details of his education, academic appointments and distinctions are available in his CV.
news
| Oct 19, 2026 | As of October 2026, Juan M. Haut serves as an Editorial Board Member of Scientific Reports. |
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| Oct 19, 2026 | In 2026, Juan M. Haut joined Remote Sensing as an Associate Editor. He has also served as Guest Editor of multiple special issues. |
| May 23, 2026 | Appointment as Tenured Associate Professor (Profesor Titular de Universidad) at the University of Extremadura, in the area of Computer Architecture and Technology. The resolution of 12 May 2026 was published in the BOE on 23 May 2026. |
selected publications
- ESWAFederated Learning Meets Remote SensingExpert Systems with Applications, 2024
- IEEE TNNLSEnhancing Distributed Neural Network Training through Node-Based CommunicationsIEEE Transactions on Neural Networks and Learning Systems, 2023
- Proc. IEEEDistributed Deep Learning for Remote Sensing Data InterpretationProceedings of the IEEE, 109(8), 1320–1349, 2021
- IEEE TGRSFLOP-Reduction through Memory Allocations within CNN for Hyperspectral Image ClassificationIEEE Transactions on Geoscience and Remote Sensing, 59(7), 5860–5876, 2021
- Neurocomp.Heterogeneous Model Parallelism for Deep Neural NetworksNeurocomputing, 441, 1–12, 2021
- IEEE TGRSCloud Deep Networks for Hyperspectral Image AnalysisIEEE Transactions on Geoscience and Remote Sensing, 57(12), 9832–9848, 2019
- ISPRSDeep Learning Classifiers for Hyperspectral Imaging: A ReviewISPRS Journal of Photogrammetry and Remote Sensing, 158, 279–317, 2019
- ISPRSA new deep convolutional neural network for fast hyperspectral image classificationISPRS Journal of Photogrammetry and Remote Sensing, 145, 120–147, 2018
