Full Professor · Universitat de València

Gustau
Camps-Valls

Working at the intersection of machine learning and Earth system science — building AI that not only predicts, but helps us understand a changing climate.

Publications Google Scholar CV ↓

IEEE Fellow ELLIS Fellow ACM Fellow AGU Fellow ESF Fellow EurASc Fellow Academia Europeae Fellow AAIS Fellow ERC Synergy ERC Consolidator Humboldt Award Blaise Pascal Medal Highly Cited Researcher

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Positions

Current &
past roles

Current

Full Professor, Electrical Engineering

Universitat de València

Group Leader, ISP at IPL

Image Processing Laboratory, UVEG

Convener, AI for Good Seminars

ITU AI for Good · United Nations

Visiting Chair Professor

Institut Polytechnique de Paris, Paris (2026-2029)

Humboldt Researcher

Max Planck Institute in Biogeochemistry, Jena (2026-2028)

Visiting & Honorary

Invited Professor

École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (2013)

Invited Researcher

Max Planck Institute (MPI) for Intelligent Systems, Tübingen, Germany (2009)

Invited Professor

Università di Trento, Italy (2005)

Invited Researcher

Universidad Carlos III de Madrid, Spain (2001)

IEEE Distinguished Lecturer

IEEE GRSS (2017–2020)

Research Vision

AI that understands
the Earth system

"My work lives at the intersection of machine learning and Earth sciences — not just to predict, but to advance our understanding of a changing climate."

I develop causal and equation discovery methods alongside hybrid models that fuse deep learning with physical laws — building more resilient, interpretable, and trustworthy Earth system models.

My path has traversed bioengineering, kernel methods for signal processing, satellite remote sensing, and now the geosciences — driven by what I call a polymathic curiosity: a genuine interest in almost everything.

Today I lead the Image and Signal Processing (ISP) group at the University of València, where we push the boundaries of AI for climate risk, extreme events, and Earth observation.

Research Pathway

A career
in five pivots

Early 2000s

Bioengineering & Support Vector Machines

PhD work optimising drug dosages for kidney transplant patients — high-dimensional data, few samples, multi-criteria objectives. An early encounter with the statistical challenges that still shape my thinking.

2005 – 2013

Kernel Methods for Image & Signal Processing

Deep work on segmentation, denoising, interpolation and compression using kernel machines. Co-authored a Wiley textbook on kernel-based digital signal processing.

2013 – 2018

Satellite Remote Sensing & Earth Observation

Applied neural networks and kernel machines to classification, parameter retrieval, anomaly and change detection from satellite imagery. Co-authored a Wiley book on ML for remote sensing. An ERC Consolidator grant started the causality revolution in Earth science.

2018 – 2022

Hybrid Models & Earth System Science

Established the paradigm of combining deep learning with physical process understanding. A 2019 Nature paper set the agenda for physics-informed ML in the geosciences. Co-authored a Wiley book on deep learning for Earth and climate sciences. An ERC Synergy grant started the field of hybrid AI for climate modeling.

2022 – Present

Causal Inference, Foundation Models & Climate Risk

Decoding the why behind extreme events — droughts, heatwaves, floods, wildfires. Building early warning systems and AI foundation models that are transparent, physically consistent, and actionable. Towards an AI that is humane, humanist and humanitarian.

My full medium.com story