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Gabriele Cavallaro (He/Him)

Associate Professor
School of Engineering and Natural Sciences
Faculty of Electrical and Computer Engineering
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VR-2 -  V02-257b
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Abstract

Gabriele Cavallaro (Senior Member, IEEE) received his B.Sc. and M.Sc. degrees in Telecommunications Engineering from the University of Trento, Italy, in 2011 and 2013, respectively, and a Ph.D. degree in Electrical and Computer Engineering from the University of Iceland, Iceland, in 2016. From 2016 to 2021, he served as the deputy head of the "High Productivity Data Processing" (HPDP) research group at the Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich, Germany. Since 2022, he has been the Head of the ``AI and ML for Remote Sensing'' Simulation and Data Lab at the JSC. From 2022 to 2024, he served as an Adjunct Associate Professor at the Computer Science Department of the University of Iceland. Since 2024, he is an Associate Professor with the Faculty of Electrical and Computer Engineering at the University of Iceland. From 2020 to 2023, he held the position of Lead for the High-Performance and Disruptive Computing in Remote Sensing (HDCRS) Working Group under the IEEE GRSS Earth Science Informatics Technical Committee (ESI TC). From 2023 to 2024, he served as Co-chair for the ESI TC. Since 2025, he has been the Chair of the IEEE GRSS Quantum Earth Science and Technology Technical Committee (QUEST TC). Concurrently, he serves as a Visiting Professor at the Φ-Lab within the European Space Agency (ESA), where he contributes to the Quantum Computing for Earth Observation (QC4EO) initiative. Additionally, he served as an Associate Editor for the IEEE Transactions on Image Processing (TIP) from 2022 to 2024. 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 include remote sensing data processing with parallel machine learning algorithms that scale on distributed computing systems and innovative computing technologies.

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Courses 2024 - 2025