Head of Simulation and Data Lab (JĂĽlich Supercomputing Centre)
Associate Professor (University of Iceland)
Prof. Gabriele Cavallaro
Affiliations
Head of Simulation and Data Lab "AI and ML for Remote Sensing" JĂĽlich Supercomputing Centre
Associate Professor, Faculty of Electrical and Computer Engineering
Visiting Professor, Φ-Lab, European Space Agency
Research Topics
Remote Sensing
High Performance Computing
Machine Learning
Quantum Computing
Guest lectures, presentations, workshops
Talks
Erasmus+ BIP Machine Learning for Earth Observation and Data Fusion
The programme aims at training professionals trained in the use of geospatial data coming from satellite for Earth Observation applications, such as the monitoring of the UN Sustainable Development Goals. It is based on a virtual mobility that provides the basic of machine learning techniques applied to satellite data sets and challenges the participants to provide answers to data processing questions in groups of students by different institutions.
Courses, lectures, materials
Teaching
Communication Engineering
Telecommunication systems are everywhere in modern societies, and great progress has been made in the field of telecommunications in recent years. The development is still going on and will be for coming years, both in terms of technology itself and its utilisation.
Calls for papers, funding, vacancies
News and events
Democratizing Foundation Models for Earth Observation Applications
To address societal challenges, a collaborative initiative involving DLR, IBM, FZJ, and KP Labs has developed the FAST-EO project. This initiative aims to enhance and support multiple Earth observation applications.
Academic papers
Recent Publications
Conference Papers
Downstream Applications on Prithvi: A Foundation Model for Global Geospatial Data
Prithvi V1.0: Generalist Geospatial Foundation Model on Global HLS Data
4M4EO – Massively Multi-Modal Masked Autoencoders for Earth Observation
Journals
Lossy Neural Compression for Geospatial Analytics: A review
Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications [preprint - not peer reviewed]
Vectorized Highly Parallel Density-Based Clustering for Applications With Noise
Book chapters
Proven Approaches of Using Innovative High-Performance Computing Architectures in Remote Sensing
Remote Sensing Data Fusion: Markov Models and Mathematical Morphology for Multisensor, Multiresolution, and Multiscale Image Classification
Analyzing Remote Sensing Images with Hierarchical Morphological Representations
About me
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I did my Erasmus at the University of Iceland, which eventually led to three years of doctoral studies and earning the title of PhD.
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Since then, I've been a research assistant at JSC - JĂĽlich Supercomputing Centre, later becoming Head of Simulation and Data Lab. Since 2024, I have been granted assistant Professorship at the University of Iceland in ReykjavĂk. I work at the intersection of Remote Sensing (RS), High Performance Computing (HPC), Quantum Computing (QC) and Machine Learning (ML).
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You can contact me at
g.cavallaro@fz-juelich.de
gcavallaro@hi.is
