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Biography

Dora B. Heras is a full professor in the Department of Electronics and Computer Engineering at the University of Santiago de Compostela (Spain). She received a MS in Physics in 1993 and was awarded a PhD cum laude from this university. In the period from 2005 to 2010 she was appointed as the head of the Sustainable Development Office at this university. Since 2008 she is also with the research centre CiTIUS (Centro de Investigación en Tecnoloxías Intelixentes) where she leads the hyperspectral remote sensing computing line and has received the accreditation as full professor in 2020. He is also co-chair of the High-Performance and Disruptive Computing in Remote Sensing (HDCRS) Working Group of the IEEE GRSS ESI Technical Committee.

Her research contributions cover a range of topics in the combined fields of image processing, remote sensing, machine learning and high performance computing. In particular, in the last ten years her research has been framed in the line of high performance computing and its application to remote sensing. She has participated in research projects funded by Spanish and European institutions, and R&D agreements.  She has served as program committee, guest editor and reviewer in several conferences, in particular, the Euromicro 2021 Parallel and Distributed Conference, and serves as reviewer for different top-ranked journals. She is also a member of the Euro-Par conference Steering Committee since 2018 and has acted as co-chair of the co-located workshops for all the editions since 2017.

Biography

Gabriele Cavallaro 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 has been the deputy head of the “High Productivity Data Processing” (HPDP) research group at the Jülich Supercomputing Centre, Germany. From 2019 to 2021 he gave lectures on scalable machine learning for remote sensing big data at the Institute of Geodesy and Geoinformation, University of Bonn, Germany. Since 2022, he is the Head of the “AI and ML for Remote Sensing” Simulation and Data Lab at the Jülich Supercomputing Centre, Forschungszentrum Jülich, Germany and an Adjunct Associate Professor with the School of Natural Sciences and Engineering, University of Iceland, Iceland. He is also the Chair of the High-Performance and Disruptive Computing in Remote Sensing (HDCRS) Working Group of the IEEE GRSS ESI Technical Committee and a Visiting Professor at the Φ-lab of the European Space Agency (ESA) in the context of the Quantum Computing for Earth Observation (QC4EO) initiative.

Since October 2022 he serves as an Associate Editor of the IEEE Transactions on Image Processing (TIP). He also serves on the scientific committees of several international conferences and he is a referee for numerous international journals. 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 distributed computing systems and cutting-edge computing technologies, including quantum computers.

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Biography

Bertrand Le Saux (Ms. Eng. 1999, MSc. 1999 INP Grenoble, PhD 2003 Univ. Versailles / Inria, Dr. Habil. 2019 Univ. Paris-Saclay) is a scientist with the European Space Agency ESRIN/Phi-lab, in Frascati (IT). He is working on data-driven techniques for visual understanding, with a background in machine learning and computer vision. He’s interested in tackling practical problems that arise in Earth observation, to bring solutions to current environmental and societal challenges. He has been a researcher at CNR/ISTI Pisa (IT), Univ. of Bern (CH), ENS Cachan (FR) and ONERA (FR). He was co-chair [2015-2017] and chair [2017-2019] for the IEEE GRSS technical committee on image analysis and data fusion (IADF TC). He is currently an associate editor of the Geoscience and Remote Sensing Letters. He is also a co-organiser of the CVPR / EarthVision workshop series.

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Biography

Alvaro Moreno-Martínez earned a Ph.D. degree in Physics (2014, summa cum laude) from the University of València, and he is currently a Senior Researcher at the Image Signal Processing Group (ISP) at the same university.  Dr. Moreno is a Google Developer Expert (GDE), and his research has been mainly focused on the development of physical and advanced machine learning models and the implementation of operational methodologies for the study of vegetation cover through satellite imagery at different spatial/temporal scales. He has published 44 papers in international peer-reviewed journals, 3 book chapters, and more than 80 international conference presentations. Dr. Moreno is an external professor of the Master of Remote Sensing and the Data Science degree, both at the University of Valencia, and he has participated in 12 projects (7 national, 5 international), and member of the European Geosciences Union, IEEE, and the American Geophysical Union.

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Biography

Emma Izquierdo-Verdiguier (Ph.D., 2014, University of Valencia) is an Assistant PostDoc in the Institute of Geomatics at the University of Natural Resources and Life Sciences (BOKU, Vienna). Dr. Izquierdo-Verdiguier is a Google Developer Expert from 2022, and her research interests are focused on the use of Earth Observation data and cloud computing environment for land surface phenology. Her previous research focused on machine learning applied to remote sensing data. In particular, nonlinear feature extraction based on kernel methods, and on automatic object identification and classification using multispectral images. She is also an external professor of the Master of Remote Sensing at the University of Valencia. In 2012, her paper was ranked second in the student’s competition of the IEEE Geoscience and Remote Sensing Symposium (IGARSS).

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