PABLO QUESADA BARRIUSO

Pablo Quesada Barriuso is a Professor at the University of Santiago de Compostela's Department of Electronics and Computing, affiliated with the Higher Technical School of Engineering. He holds a PhD in Information Technology (2015, Cum Laude) from the same institution, focusing on real-time spectral-spatial classification of n-dimensional images using GPUs. His research emphasizes parallel computing techniques for hyperspectral/multispectral remote sensing data processing, targeting low-cost devices to optimize real-time analysis and storage efficiency.

Research interests include GPU-accelerated algorithms, wavelet-based denoising, mathematical morphology, and deep learning applications for environmental monitoring. He has been part of the Computer Architecture Group since 2010, contributing to projects like the Galician Rivers Multispectral Anomaly Detection Dataset and CGAN-based reconstruction models.

His publications (2013-2025) highlight innovations in superpixel segmentation, watershed algorithms on GPUs, and ELM-based classification systems. While no awards are explicitly listed, his work demonstrates significant contributions to efficient GPU computing for remote sensing challenges.

Advising and grants information is not detailed in the provided text. His work is closely tied to the ARQCOMP (Computer Architecture) research group, exploring hardware-software co-design for high-performance imaging solutions.