AI for Earth and Climate: From satellite pixels to causal insights for effective action
AI for Good Webinar Series - ITU, Online, 2025
Invited talks
AI for Good Webinar Series - ITU, Online, 2025
Advances in Representation Learning for Earth Observation
REO Workshop at EurIPS 2025, Copenhagen, Denmark, 2025
Blaise Pascal Medal Keynote: Physics-aware Machine Learning for the Climate
EurASc Symposium and Ceremony 2025, CERN, Geneva, Switzerland, 2025
Physics-aware Machine learning for Earth observation
Tackling Climate Change with Machine Learning Workshop, NeurIPS 2024, Vancouver, Canada, 2024
Harnessing Digital Innovation for Resilience in the Context of Climate Change
9th Multi-stakeholder Forum on Science, Technology and Innovation for the SDGs (STI Forum), UN Headquarters, New York, USA, 2024
IA para unas Ciencias de la Tierra sostenibles
ELLIS / AI CSIC Hub Workshop, València, 2024
Hybrid and Causal ML in the Earth sciences
Artificial Intelligence Doctoral Academy (AIDA) - Lecture Series, Online, 2024
Living in the ML-Physics Interplay for the Earth sciences
Cambridge University - Dep. Engineering, Cambridge, UK, 2023
Hybrid and Causal ML in the Earth sciences
Google Deepmind, London, UK, 2023
AI for the Earth sciences
IAHR World Congress 2023, Vienna, Austria, 2023
Evaluation of Dimensionality Reduction Approaches for Optical Water Type Classification using EnMAP
Machine Learning And Data Analysis In Oceanography. 2023 edition of the Liège Colloquium, University of Liège, Place du XX-Août, 7 - 4000 Liège - Belgium, 2023
Machine learning for modeling and understanding the Earth system
Summer school, ESSAI/ACAI 2023, Ljubljana, Slovenia, 2023
AI for Sustainable Earth Sciences
IbPRIA 2023, Alacant, 2023
Advancing AI for Urban Sustainability
Joint Urban Remote Sensing Event, Heraklion Crete, Greece, 2023
Causal Inference for Disaster Management
Workshop on AI for Disaster Management - ESA philab, Frascati, Italy, 2023
Graphs in State-Space Models for Granger Causality in Climate Science
CausalStats23: When Causal Inference meets Statistical Analysis, Paris, 2023
A collective AI agenda for Earth Observation
Catalonia AI4EO Day, Barcelona, 2023
The role of AI in Digital Twins
Winter 2022/2023 Workshop at Lorentz Center, Leiden, NL, 2023
Physics-aware Machine Learning for Earth Observation
NeurIPS 2022 - Workshop on Tackling Climate Change with Machine Learning, New Orleans, 2022
Advancing AI for modeling and understanding the Earth system
Advancing AI for modeling and understanding the Earth system, E4C - Institut Polytechnique de Paris, 2022
Advancing AI for modeling and understanding the Earth system
ETN iMIRACLI - Summer school, Stockholm, Sweden, 2022
A collective agenda for AI on the Earth sciences
A collective agenda for AI on the Earth sciences - AI and Climate Science, Online talk - ITU-UN AI4Good seminar series, 2022
Physics-aware machine learning and causality for the Earth sciences
ML and Remote Sensing Discussion Group, Online talk, 2021
Gaussianizing the Earth
KITP Conference: Machine Learning for Climate, Online talk, 2021
Machine Learning for Earth and Climate Sciences
GIMM: Europe - Side Event. The challenge of GEOAI for Good & GEOAI for a Sustainable Europe, Online talk, 2021
Interpretability and Causality in Earth Sciences (aka "fitting is not enough")
ESA Phi-Week Workshop, Online talk, 2021
Physics-aware Machine Learning for the Earth sciences
Climate Change AI - Machine Learning for Earth and Climate Sciences, Online talk, https://www.climatechange.ai/, 2021
Advances in Machine Learning for Modelling and Understanding in Earth Sciences
MACLEAN workshop, Online talk, 2021
Advances in Machine Learning for Modelling and Understanding in Earth Sciences
IEEE GRSS - Italian chapter, Online talk, Italy, 2021
Living in the Physics and Machine Learning Interplay for the Earth Sciences
UTHZ Seminar series, Online talk, Zurich, 2021
Physics-aware Interpretable Machine learning in the Earth sciences
OCEANIX Seminar series, Online talk, France, 2021
Physics Aware Machine Learning for the Earth Sciences
MPML Seminar series - ELLIS seminar, Online talk, Lisboa, 2021
DeepCube: Explainable AI Pipelines for Big Copernicus data
BiDS Big Data from Space, Online Everywhere, https://www.bigdatafromspace2021.org/, 2021
Living in the Physics and Machine Learning Interplay - An AI agenda with examples for the DTE
The ESA Phi-week 2020, ESA-ESRIN, Italy, 2020
Living in the Physics – Machine Learning Interplay for Earth Observation
AAAI Fall Series 2020 Symposium on Physics-guided AI for Accelerating Scientific Discovery, 2020
Advancing Deep Learning For Earth Sciences: From Hybrid Modeling To Interpretability
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, Hawaii, USA, 2020
Gaussianization for Earth - An Information Theoretic Perspective
Machine Learning for Science and Engineering (MLSE) 2020, Online Everywhere, https://www.mlse2020.com/earth, 2020
How to Surf the Physics and Machine Learning Interplay
Machine Learning for Science and Engineering (MLSE) 2020, Online Everywhere, https://www.mlse2020.com/earth, 2020
Living in the Physics-Machine learning interplay for earth observation
InGARSS 2020, Online Everywhere, https://www.ingarss2020.org/, 2020
Advances in Machine Learning for Earth Sciences
Sustainable AI in practice 2020, Online Everywhere, https://www.conferencemanager.dk/sustainableai/conference/, 2020
Advances in Machine Learning for Earth Observation
Dept Geography – University of Zurich, Switzerland, Dept Geography – University of Zurich, Switzerland, 2020
Advances in Machine Learning for Earth Sciences
UGent Data Science Seminar – University of Ghent, Belgium, UGent Data Science Seminar – University of Ghent, Belgium, 2020
Advances in Machine learning for Modelling and Understanding in Earth Sciences
Severo Ochoa Research Seminars – Barcelona Supercomputing Center (BSC), Barcelona, Severo Ochoa Research Seminars – Barcelona Supercomputing Center (BSC), Barcelona, 2020
Multivariate Gaussianization: Information Bottleneck and Flows
Technical University of Berlin, Germany, Technical University of Berlin, Germany, 2019
HISTARFM: High spatial resolution land products from Landsat reflectance time series in GEE
eo for Good 2019, Google, SF, Geo for Good 2019, Google, SF, 2019
Physics-aware Machine Learning for Earth Observation
https://www.wur.nl/en/Research-Results/Chair-groups/Environmental-Sciences/Laboratory-of-Geo-information-Science-and-Remote-Sensing/Show/Earth-Observations-and-Terrestrial-Carbon-Cycling.htm, Wageningen University and Research, Wageningen, The Netherlands, 2019
Towards Physics-aware Machine Learning for Earth Observation
Indian Statistical Institute, Kalkota, India, Indian Statistical Institute, Kalkota, India, 2019
Physics-aware Machine Learning and Causal Inferece in Earth and Climate Sciences
ISI, Bangalore, India, ISI, Bangalore, India, 2019
Advances in Machine Learning for Earth Observation
CEPT, Ahmedabad, India, CEPT, Ahmedabad, India, 2019
New Machine Learning for Earth and Climate Sciences
ISI, Mumbai, India, ISI, Mumbai, India, 2019
Revisiting global teleconnections of ENSO over soils and vegetation
ESA Living Planet Symposium, 2019, ESA Living Planet Symposium, 2019, 2019
Learning nonlinear feature representations from Earth data
EGU, EGU 2019, 2019
Advances in Machine Learning for Earth Observation
2019
Machine Learning for Earth Observation
Cavanilles Institute of Biodiversity and Evolutionary Biology, Cavanilles Institute of Biodiversity and Evolutionary Biology, Valencia, 2019
Copernicus Imaging Microwave Radiometer (CIMR) Land Science and Products
Low-Frequency Microwave Continuity Workshop - JPL, USA, Low-Frequency Microwave Continuity Workshop - JPL, USA, 2019
HyperLabelMe: Benchmarking Image Classifiers
The Phi-week - EO Open Science and Future EO - ESA-ESRIN, Italy, The Phi-week - EO Open Science and Future EO - ESA-ESRIN, Italy, 2018
Physics-aware And Explainable Machine Learning
The Phi-week - EO Open Science and Future EO - ESA-ESRIN, Italy, The Phi-week - EO Open Science and Future EO - ESA-ESRIN, Italy, 2018
Statistical Distillation of the Earth System Data Cube
The Phi-week - EO Open Science and Future EO - ESA-ESRIN, Italy, The Phi-week - EO Open Science and Future EO - ESA-ESRIN, Italy, 2018
Machine Learning for Climate: 15 ways to leave your lover
2018
From sparsity to Gaussianization in neural networks
2018
Physics-driven Gaussian Processes for Earth Observation
2018
Machine learning for Earth Observation
2018
Neural networks, Gaussianization, and information distillation
2018
Unsupervised Deep Networks: Sparsity, Gaussianization, and the information bottleneck
2018
Unsupervised Deep Feature Learning with Sparse Codes and Gaussianization
2018
Unsupervised Deep Networks: Neural networks, Gaussianization, and information distillation
2018
Gaussianization, Independence, Fairness
2018
Machine Learning in Remote Sensing
2017
Advanced Machine Learning for Biophysical Parameter Retrieval
2017
Open problems in remote sensing
2017
Large Scale Gaussian Processes for Atmospheric Parameter Retrieval and Cloud Screening
American Geophysical Union (AGU) Fall meeting 2017, New Orleans, USA, 11-15 December 2017, 2017
Advanced Machine Learning Emulators of Radiative Transfer Models
American Geophysical Union (AGU) Fall meeting 2017, New Orleans, USA, 11-15 December 2017, 2017
Mapping wood density globally using remote sensing and climatological data
American Geophysical Union (AGU) Fall meeting 2017, New Orleans, USA, 11-15 December 2017, 2017
Physics-Aware Gaussian Processes for Earth Observation
2017
Physics-aware machine learning for biophysical parameter retrieval
2017
Potential of Machine Learning for FLUXCOM upscaling
2017
Vegetation Monitoring with Gaussian Processes and Latent Force Models
2017
Latent Force Models for Model-Data Integration in Vegetation Monitoring
2017
Monitoring Vegetation From Space with Gaussian Processes and Latent Force Models
2016
Machine learning for Remote Sensing
2016
Semisupervised manifold alignment with kernels
2016
Domain Adaptation with the Kernel Manifold Alignment
2016
The role of modern machine learning in Earth observation
2015
Monitoring Earth Climate Variables with Statistical Inference
2015
Learning Structures in Earth Observation Data with Gaussian Processes
2015
Kernel manifold alignment
2015
Visual Illusions: Sometimes it is better not to see the truth!
2015
Geometrical and Statistical Properties of Vision Models obtained via MAximum Differentation
2015
Hyperspectral image processing
2014
Advances in Kernel Methods for Remote Sensing Image Processing
2014
Kernel methods for hyperspectral image processing
2014
Computational Visual Neuroscience: New Perspectives from Statistical Learning
2014
Back to the 60s: Kernel Methods to Deep Neural Networks in Remote Sensing Data Processing
2013
Recent machine learning developments for remote sensing data processing
2013
Advances in Kernel Image Processing
2013
Phase in images: a summary of statistical facts
2013
Fitting multi-layer models using MAximum Differentation (MAD)
2013
Iterative Gaussianization Framework for Image Processing
2012
Extended Kernel Methods
2012
Kernel Signal-To-Noise Ratio for Machine Learning
2012
Statistical Learning in Earth Monitoring
2012
Multivariate Gaussianization for data processing
2012
SVM for remote sensing image classification: tricks of the trade
2011
Iterative Gaussianization Framework
2009
Natural Image Relations in Denoising
2009
Natural Image Relations in Kernel-based Image Denoising
2009
Kernel Classifiers in Remote Sensing
2008
Color and Luminance Discrimination by Non-Linear PCA
2008
Masking-like Non-Linearities from Non-linear PCA
2008
Kernel-based Data Fusion
2007
Kernel methods in Bioinformatics
2006
Kernel Methods in Remote Sensing: Introduction, Applications and Research Opportunities
2005
Perturbation Analysis of the Changes in V1 Receptive Fields due to Context
2004