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Biographies

Miguel-Ángel Fernández-Torres
Assistant Professor, Signal Theory and Communications Department, Universidad Carlos III de Madrid

Miguel-Ángel Fernández-Torres has a degree in Audiovisual Systems Engineering, a Master degree in Multimedia and Communications, and a Ph.D. in Multimedia and Communications from Universidad Carlos III de Madrid, Spain, in 2013, 2014, and 2019, respectively. Presently, he works as an Assistant Professor at the Signal Theory and Communications Department of Universidad Carlos III de Madrid, Spain, after having finished a postdoctoral stage at the Image and Signal Processing Group at the Universitat de València, Spain. His current research in Machine Learning for Earth and Climate Sciences involves designing and understanding explainable deep generative models and machine attention mechanisms to be deployed for anomaly and extreme event detection. Previously, he has participated in other projects within the Computer Vision field, which includes spatio-temporal visual attention modeling and understanding, image and video analysis, and medical image analysis and classification. He also studied at Technische Universität Wien, Vienna, Austria, during his Bachelor's degree, in 2013, and did two research stays at the Visual Perception Laboratory of Purdue University, West Lafayette, Indiana, USA, and the International Future Lab AI4EO at Technische Universität München, Munich, Germany, in 2016 and 2022, respectively.

Michela Ravanelli

AXA Research Fund-IOC UNESCO fellow, Sapienza University of Rome

Michela Ravanelli holds a BSc and MSc in Environmental Engineering and a PhD in Geodesy from Sapienza University of Rome. Previously, she was a visiting researcher at NASA JPL (USA) and the IPGP (France), where she also served as a CNES postdoctoral fellow. Currently as an AXA Research Fund-IOC UNESCO fellow, she focuses on the joint use of real-time GNSS ground and ionospheric monitoring to improve tsunami early warning systems. Her research focuses on GNSS geodesy, ionospheric sounding, remote sensing, and machine learning, with an emphasis on monitoring and detecting natural hazards.

Luca Brocca
National Research Council of Italy

Luca Brocca received the Master's degree and the PhD in Civil Engineering in 2003 and 2008 respectively. Since (2009) 2019 he is (Researcher) Director of Research at the National Research Council, Research Institute for Geo-Hydrological Protection of (CNR-IRPI) in Perugia. He is author and co-author of 200+ journal refereed papers (21000+ citations), 80+ papers in peer-reviewed conference proceedings/book chapters, and 10+ regional and global datasets. Luca Brocca is the head of the Hydrology Next Group at CNR-IRPI and he is involved as PI (and co-PI) in several projects funded by the European Commission and Space Agencies (ESA, EUMETSAT). Among others, in 2012, he received the “Early Career Research Excellence" award by iEMSs society, in 2018 he has been the winner of the Copernicus Masters competition “BayWa Smart Farming Challenge", in 2019 and 2020 he has been nominated “Highly Cited Researchers" by Web of Science Group – Clarivate, and in 2021 he won the “ESA–EGU Earth Observation Excellence Award". The main research interest of Luca Brocca lies in the development of innovative methods for exploiting satellite observations (soil moisture, rainfall, river discharge) for hydrological applications including floods, landslides, rainfall, droughts, irrigation, water resources management (e.g., SM2RAIN, irrigation from space), and he is recognized expert in digital twin technology for hydrology (DTE Hydrology).

Noel Borlongan

Philippines Space Agency

Noel is a Senior Science Research Specialist in the Space Data Mobilization and Applications Division of the Philippine Space Agency. His work focuses on leveraging satellite imagery and geospatial technologies for various applications, particularly in disaster risk reduction and management. This includes monitoring and assessing natural hazards such as floods, landslides, oil spills, and burned areas to support timely response and mitigation efforts. Beyond disaster applications, he has been actively involved in projects related to land cover mapping, ground motion monitoring, and the integration of artificial intelligence (AI) for object detection in satellite images. Through his works, he aims to advance the use of space-based solutions for disaster resilience, environmental monitoring, and resource management.

Nikolaos Dionelis
Internal Research Fellow (IRF), the European Space Agency (ESA)

Nikolaos Dionelis is currently an Internal Research Fellow (IRF) at the European Space Agency (ESA), at the Φ-lab in ESRIN, Italy (since 1 April 2023). He was previously a Post-Doc Research Associate in Machine Learning at the University of Edinburgh and the University Defence Research Collaboration (UDRC) in Signal Processing which is a consortium of companies and universities in the UK including Thales and Leonardo (3/2019 - 3/2023). He has PhD and Masters MEng degrees from Imperial College London (2011-2015 and 2015-2019). He is enthusiastic about collaborating in projects to contribute to Earth Observation (EO) science. In his current position, the broad aim is to develop new models for AI for Earth Observation (AI4EO). Specifically, his focus has been twofold: Firstly, he develops new methodologies in AI that greatly facilitate progress toward important goals such as performing tasks that are “downstream” from EO data and lead to useful indicators and insights. Examples of such tasks that are accomplished by EO Foundation Models are building density regression for monitoring urban growth, road segmentation, land cover mapping and flood segmentation. Secondly, he develops practically useful solutions to some specific and technically challenging applications for sustainability and climate such as the estimation of the age of buildings from multi-modal EO and street-view image datasets and the reconstruction of the ice sheet in Greenland. His background is in deep learning and computer vision. He has experience in: i) deep discriminative classifier models, including Convolutional Neural Networks (CNN), Residual Networks (ResNet) and Transformer models, and ii) deep generative models, including Generative Adversarial Networks (GAN), flow-based models, Variational Autoencoders (VAE) and diffusion models.”

Nicla M. Notarangelo
Marie Skłodowska-Curie Actions Postdoctoral Fellow, WEO Luxembourg

Nicla M. Notarangelo is a Marie Skłodowska-Curie Actions Postdoctoral Fellow at WEO, specializing in artificial intelligence and computer vision for urban sustainability, cultural heritage, and smart city applications. With a PhD in Engineering for Innovation and Sustainable Development and an MSc in Architectural Engineering, she has contributed to interdisciplinary research across industrial and academic organizations, including the University of Basilicata, Beijing Jiaotong University, and Japan National Research Institute for Earth Science and Disaster Resilience. Passionate about the societal relevance of science, she is committed to open science and advancing research with real-world impact.

Maria J. Molina
Assistant Professor in the Department of Atmospheric and Oceanic Science at the University of Maryland, College Park

Dr. Maria J. Molina is an Assistant Professor in the Department of Atmospheric and Oceanic Science at the University of Maryland, College Park. She is also affiliated with the Artificial Intelligence Interdisciplinary Institute at Maryland, the University of Maryland Institute for Advanced Computer Studies, and the National Science Foundation (NSF) National Center for Atmospheric Research. Maria's research spans machine learning for weather and climate applications, including prediction, predictability, and signal detection. Maria serves as a member of the US CLIVAR Predictability, Predictions, and Applications Interface panel, the WCRP Scientific Steering Group for the Earth System Modeling and Observations (ESMO) core project, and the CMIP7 Controlled Variables Task Team. Recently, Maria earned the NASA Early Career Investigator Program in Earth Science award.

Karl Payne
Lecturer and Stream Coordinator for Water Resources Management, University of West Indies

Dr. Karl Payne is a Lecturer and Stream Coordinator for Water Resources Management at the Centre for Resource Management and Environmental Studies, University of the West Indies, Cave Hill, Barbados. Dr. Payne's research is focused on climate-resilient water resources management, blending artificial intelligence, data analytics, and systems thinking to drive innovative, science-based solutions for small island developing states (SIDS). Holding a Ph.D. in Water Resources Engineering from the University of South Florida, he has over ten years of experience spanning academia and industry, collaborating with interdisciplinary teams to develop cutting-edge solutions that leverage machine learning for data-driven decision making. Dr. Payne's research has been published in leading journals including Environmental Science and Technology, Water Research, Physical Review E, and Hydrology.

Shruti Nath
Post-Doctoral Researcher, University of Oxford

Shruti Nath is a Post-Doctoral Researcher at the University of Oxford, Department of Physics. With a background in mathematics and a PhD in climate model emulation, her research now focusses on using data-driven, AI techniques for improving weather forecasts, particularly rainfall. She collaborates closely with Climate and Meteorological bodies within the Greater Horn of Africa, where the potential of AI to improve forecasts is great due to its low computational costs as compared to traditional weather models. She strongly engages in regional work and capacity building with a lens towards cloud-optimised AI approaches. She is also a lecturer for AI in Climate Sciences at the African Institute for Mathematical Sciences.

Patrick Ebel
Internal Research Fellow, ESA

Patrick Ebel is an Internal Research Fellow at ESA Φ-lab. Before joining Φ-lab, Patrick conducted research on keypoint matching for photogrammetry, multi-sensor satellite image reconstruction and change detection for Earth observation. He received his MSc degree in Artificial Intelligence from Radboud University Nijmegen and his PhD degree in Remote Sensing from Technical University of Munich. His scientific interests are in utilizing machine learning and globally deployed sensors to monitor our planet, in order to predict and respond to its changing environment at any place and point in time. With Φ-lab, Patrick’s research focus is on anticipating the effects of extreme weather situations and enabling time

Giriraj Amarnath
Principal Researcher, International Water Management Institute (IWMI)

Giriraj Amarnath is a Principal Researcher in Disaster Risk Management and Climate Resilience and the Interim Deputy Director of the CGIAR Climate Action Science Program at the International Water Management Institute (IWMI) in Colombo, Sri Lanka. With over 24 years of experience, he has led climate resilience and adaptation initiatives across 25+ countries, working with governments, NGOs, communities, and the private sector.

Currently, he spearheads an innovative climate resilience program focused on anticipatory action to mitigate climate shocks. His work integrates climate risk insurance, satellite-based monitoring and early warning systems, emergency response, digital innovation, disaster risk reduction, and climate-smart food and water security solutions. He is also co-developing an AI-enabled chatbot for flood and drought mitigation, leveraging near real-time Earth observation data and human-centered agricultural contingency planning. Giriraj holds a Ph.D. in Applied Remote Sensing and Natural Resources Management and served as a visiting faculty at the Symbiosis Institute of Geoinformatics in Pune, India. He has authored over 120 research publications spanning climate services, agriculture, disaster risk management, and natural resources management.

Ronan McAdam
Junior Scientist, CMCC Foundation

Ronan McAdam is a Junior Scientist at the CMCC Foundation - Euro-Mediterranean Centre on Climate Change, working on predictions of extreme climate events. His scientific interests include forecasting, physical oceanography, climate science and the development of user-relevant applications. Since joining the CMCC in 2019, he has driven progress in the validation of essential climate variables (e.g. temperatures) in short-term and seasonal forecasting systems. He has focused particularly on marine heatwaves, defining subsurface indicators and performing global scale validations of marine seasonal forecasts. He also contributes to ocean modelling activities, studying the variability of physical variables the CMCC’s state-of-the-art high-resolution physical ocean models and reanalyses. Currently, he is developing AI-enhanced forecasts of atmospheric heatwaves, using cutting-edge technique to identify predictors and make data-driven predictions. He is involved in a range of European projects on forecasting and monitoring of extremes, ocean modelling and the use of machine learning in climate science, including EuroSea, CLINT, and ObsSea4Clim.

Filippo Catani
University of Padua

Filippo Catani, PhD, is Full Professor of Engineering Geology and Director of the “Machine Intelligence and Slope Stability Laboratory” (MISSlab) with the Department of Geosciences of the University of Padova. He is Council Member of FOMLIG (Future of Machine Learning in Geotechnics, est. 2024). Since 2016 he is UNESCO Chair Associate on the Prevention and Sustainable Management of Geo-Hydrological Hazards at the University of Florence (Italy). He is Invited Professor of Landslide Monitoring and Early Warning at the Korean Institute of Geoscience and Mineral Resources (KIGAM, South Korea), and at the SKLGP of Chengdu University of Technology (China). He is member of NASA-JPL informal group on Earth Surface Changes. He is member of the Scientific Committee of the Centre of Civil Protection of the University of Florence, ERASMUS Program Delegate for the Master Program in Water and Geological Risk Engineering at the University of Padova, and member of the Scientific Board of the Italian Branch of IAEG. He is Editor for the NHESS journal. His recent research interests are focused on the application of artificial intelligence methods to slope stability, the combination of numerical modelling and deep learning for the analysis of failure conditions on natural and man-made slopes, and the use of advanced remote sensing methods for slope monitoring and landslide forecasting at all scales. Education - After graduating with a MSc in Geology and Mineral Exploration at the University of Florence, FC received a post-graduate degree in Computer Sciences (University of California, Berkeley, 1994) and a PhD in Engineering Geology (Politecnico of Milan, University of Padua, and Ferrara, 1997). He has been post-doc researcher at the Massachusetts Institute of Technology with the Parson’s Lab Hydrology Group (1998-1999)

James Parr
Founder and CEO, Trillium Technologies

James is the founder and CEO of Trillium Technologies - a technology contractor that specialises in the application of AI and cybernetics to grand challenges, such as climate change, violent extremism, cancer and obesity, deforestation, disaster response, space weather, human spaceflight and planetary defence. Trillium’s NIO.space platform achieved the first ML trained in orbit and the first demonstration of ML for methane retrievals from orbit.

He is founder of the Frontier Development Lab (FDL), an AI research lab partnership with ESA in Europe (ESLab.ai), the LSA and NASA in the USA. FDL has achieved over 50 applied AI firsts over 10 years. FDL and NIO.space were recognised for excellence in AI and space at the 2023 Cog X awards. He lives in London with his wife and twin daughters.

Sabrina Amrouche
Co-founder AfriClimate AI, Head of Data Science at ZYTLYN

Dr. Sabrina Amrouche is the co-founder of AfriClimate AI, a nonprofit organization working to enhance the accuracy and reliability of weather forecasting models across Africa. She is leading AfriNet, a community-driven initiative to deploy weather stations across the continent and enable the development of precise, region-specific weather forecasts crucial for climate risk mitigation and resilience. Dr. Amrouche holds a PhD from CERN, where her research focused on leveraging AI for advancements in particle physics. She is currently head of the data science department at ZYTLYN, a startup transforming the travel industry through AI.

Casper Fibaek, PhD
Earth Observation Application Specialist, European Space Agency

Dr. Casper Fibaek is an Earth Observation Application Specialist at the European Space Agency, where he serves as the project manager for two key EU-funded initiatives: CopPhil, which establishes national Copernicus capacity in the Philippines through a data mirror site and pilot applications for disaster risk reduction and environmental management, and SCOPE Digital, which scales this model to the ASEAN region, piloting EO services and capacity building in Indonesia and Thailand to foster broader EU-ASEAN cooperation. With extensive experience in artificial intelligence and its applications for Earth Observation and international cooperation, Dr. Fibaek has led impactful initiatives, such as developing AI-driven solutions for African financial institutions and managing ESA's contribution to the GIGA project with UNICEF and ITU to connect schools globally. He also collaborates on AI Foundation models for satellite data to advance sustainable development initiatives. Passionate about leveraging EO technologies for societal impact, Dr. Fibaek has lectured extensively, fostering knowledge exchange in Southeast Asia, Africa, and beyond.