Department of Engineering
Gabriel Martin is Senior Research Associate with the Laing O’Rourke Centre for Smart Infrastructure and Construction, his research interests include the development and efficient implementation of new machine learning methods for image processing applied to remote sensing. He is focused on the development of new deep learning methods applied to time-series InSAR data with infrastructure health monitoring applications. He was a Predoctoral Research Associate (funded by the Spanish Ministry of Science and Innovation) with the Hyperspectral Computing Laboratory and Postdoctoral Researcher in “Instituto de Telecomunicaçoes” Lisbon, Portugal. He has obtained several prizes for his PhD dissertation such as the “Best Iberian PhD dissertation in Information System and Technologies” awarded by the Iberian Association for Information Systems and Technologies and the “Outstanding PhD Dissertation award” by the University of Extremadura.
 Martín, G., & Plaza, A. (2012). Spatial-Spectral Preprocessing Prior to Endmember Identification and Unmixing of Remotely Sensed Hyperspectral Data. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 5(2).
 Martín, G., Bioucas-Dias, J. M., & Plaza, A. (2014). HYCA: A new technique for hyperspectral compressive sensing. IEEE Transactions on Geoscience and Remote Sensing, 53(5), 2819-2831.
 Sánchez, S., Paz, A., Martín, G., & Plaza, A. (2011). Parallel unmixing of remotely sensed hyperspectral images on commodity graphics processing units. Concurrency and Computation: Practice and Experience, 23(13), 1538-1557.