High-performance and Disruptive Computing in Remote Sensing (HDCRS): a new working group of the GRSS Earth Science Informatics Technical Committee

High-performance and Disruptive Computing in Remote Sensing (HDCRS): a new working group of the GRSS Earth Science Informatics Technical Committee

Webinar Speaker: Gabriele Cavallaro (Forschungszentrum Jülich)

Gabriele Cavallaro

About the Webinar

This webinar will introduce the new working group “High-performance and Disruptive Computing in Remote Sensing” (HDCRS) of the GRSS Earth Science Informatics Technical Committee (ESI TC). The main objective of HDCRS is to connect a community of interdisciplinary researchers in remote sensing who are specialized on high-performance and distributed computing, disruptive computing (e.g., quantum computing) and parallel programming models with specialized hardware (e.g., GPUs, FPGAs). The activities of the working group for 2021 include educational events, special sessions and tutorials at conferences and publication activities, which will be presented along with its new website.

Speakers’ Bio

Gabriele Cavallaro received the B.Sc. and M.Sc. degrees in telecommunications engineering from the University of Trento, Italy, in 2011 and 2013, respectively, and the Ph.D. degree in electrical and computer engineering from the University of Iceland, Iceland, in 2016. He is currently the deputy head of the ‘‘High Productivity Data Processing’’ (HPDP) research group at the Jülich Supercomputing Centre, Forschungszentrum Jülich, Germany. Since 2021, he is the chair of the High-Performance and Disruptive Computing in Remote Sensing (HDCRS) Working Group of the IEEE GRSS ESI Technical Committee.

He was the recipient of the IEEE GRSS Third Prize in the Student Paper Competition of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2015 (Milan – Italy). His research interests cover remote sensing data processing with parallel machine learning algorithms that scale on high performance and distributed systems. He serves on the scientific committees of several international conferences and he is a referee for numerous international journals. Since 2019 he gives lectures on scalable machine learning for remote sensing big data at the Institute of Geodesy and Geoinformation, University of Bonn, Germany.

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