Caroline Gevaert
Keynote Title: Responsible AI for Earth Observation
Caroline Gevaert is an Associate Professor at the University of Twente and a part-time advisor for the World Bank, specializing in geospatial artificial intelligence (GeoAI) for sustainable development. After earning a BSc from Wageningen University, she pursued dual MSc degrees in Earth Observation (University of Valencia) and Geographical Information Systems (Lund University), followed by a cum laude PhD at the University of Twente.
Her PhD research on drone-based GeoAI for slum upgrading received the prestigious NCG JM Tienstra Research Award and earned them a spot in the New Scientist top 15 Science Talents from Belgium and the Netherlands. Rapidly advancing to Associate Professor within five years of her PhD, Caroline has secured major grants, including a personal research grant (NWO-Veni) for integrating Responsible AI into GeoAI and an NWO-MVI project with 510, an initiative of the Netherlands Red Cross and UNICEF on ethical AI for disaster response. She is member of the Dutch Academy of Sciences (KNAW) Dutch Young Academy and the Dutch Academy of Sciences Council for Natural and Technical Sciences.
Her research focuses on developing GeoAI methods tailored to Low- and Middle-Income Countries, tackling challenges such as data scarcity, urban complexity, bias mitigation, and explainability to ensure these technologies support real-world decision-making in critical development contexts.
Christian Igel
Keynote Title: Machine learning for large-scale ecosystem monitoring
Christian Igel is professor at DIKU, the Department of Computer Sciences at the University of Copenhagen. He studied Computer Science at the Technical University of Dortmund. In 2002, he received his Doctoral degree from the Faculty of Technology, Bielefeld University, and in 2010 his Habilitation degree from the Department of Electrical Engineering and Information Sciences, Ruhr-University Bochum. From 2003 to 2010, he was a junior professor for Optimization of Adaptive Systems at the Institut für Neuroinformatik, Ruhr-University Bochum. Before becoming a full professor at DIKU in 2014 he was appointed professor with special duties in machine learning at DIKU from October 2010.
He is director of the SCIENCE AI Centre, a co-lead of the Pioneer Centre for Artificial Intelligence and a Fellow of ELLIS, European Lab for Learning and Intelligent Systems. In addition, he is editor of the German Journal on Artificial Intelligence (KI) and an Associate Editor of the Evolutionary Computation Journal (ECJ) and the Artificial Intelligence Journal (AIJ).
His main research area is machine learning with a paritcular interest in support vector machines and other kernel-based methods, evolution strageties for single- and multi-objective optimization and reinforcement learning; PAC-Bayesian analysis of ensemble methods, deep neural networks, stochatic neural networks, as well as the applicaiton of machine learning to achieve SDGs.
Maria Vakalopoulou
Keynote Title: To be announced
Maria Vakalopoulou is an Assistant Professor (since 2019) and the team lead of the βiomathematics group at MICS laboratory of CentraleSupelec University Paris-Saclay, Paris, France and she is also affiliated with INRIA Saclay and Archimedes Unit, Athens, Greece. Prior to that she was a postdoctoral researcher on CentraleSupelec (2017-2019) while she received her Ph.D from the school of Rural, Surverying and Geoinformatics Engineering at NTUA (2017), where she also received her engineering diploma.
Her research is focusing on artificial intelligence with focus on the development of methods and algorithms for visual perception including remote sensing and medical imaging. The last 5 years, her research is focusing on the development of novel and robust algorithms for cancer treatment in close collaboration with clinicians in France and in particular Gustave Roussy and AP-HP hospitals. In particular, her interests include self and unsupervised and generative learning as well as training with limited amount of data.
Her research has been published in more than 23 journal papers including The Lancet Oncology (IF 54.43), Radiology (IF 29.15), Medical Image Analysis (IF 8.54), Transactions on Computational Biology and Bioinformatics (IF 3.71), while her research contributions have received number of awards and honors.
Bertrand Le Saux
Keynote Title: Destination Earth: building a digital replica of the Earth system
Bertrand Le Saux is policy officer for Green Deal (Destination Earth) and AI applications in DG CNECT at the European Commission. He is interested in tackling practical problems that arise in Earth observation and Earth sciences, to bring solutions to current environment and society challenges.
He received the Ms.Eng. and M.Sc. degrees in electrical engineering from Institut National Polytechnique, Grenoble, France, in 1999, the Ph.D. degree in computer science from the University of Versailles/Inria, Versailles, France, in 2003, and the Dr. Habilitation degree in physics from the University of Paris-Saclay, Saclay, France, in 2019. He has been for long a senior scientist working in the field of AI for Earth with ONERA the French Aerospace Laboratory in France and with the European Space Agency ϕ-lab in Italy. Dr. Le Saux was Co-Chair (2015–2017) and chair (2017–2019) for the IEEE GRSS Technical Committee on Image Analysis and Data Fusion, and an Associate Editor of the Geoscience and Remote Sensing Letters (2019-2024). He co-organised many workshops and events in machine learning x Earth observation, notably the CVPR Earth Vision workshop series, the ESA-ECMWF workshop series on Machine Learning for Earth System Observations and Predictions, and the Humanitarian Assistance and Disaster Response (HADR) workshop. https://blesaux.github.io/
