The physicist and professor of electronic engineering at the University of Valencia, has been elected a member of the European Committee of Space Sciences (ESSC) of the European Science Foundation (ESF). Its main function will be to promote the activities of Artificial Intelligence and machine learning in its application to geosciences, environmental sciences and climate.
Gustau Camps-Valls, coordinator of the Image Signal Processing (ISP) group at the Image Processing Laboratory (IPL) of the University of Valencia and an expert in Big Data processing and machine learning, will be particularly concerned with developing space applications related to topics such as climate change and the environment, of great impact on society.
The ESF is an international non-governmental, non-profit association created in France in 1974 and committed to promoting the highest quality science in Europe and promoting research and innovation.
The European Space Science Committee provides advice to the European Space Agency (ESA), the European Commission, EU national space agencies and other space decision-makers and related applications. It has become an independent scientific body of reference in Europe in space matters and a meeting point for international research collaboration.
The appointment of Camps-Valls took place last November 30 during the 62nd plenary meeting of the ESSC.
Gustau Camps-Valls’ work focuses mainly on the development of machine learning algorithms for the analysis of remote sensing data, Earth observation and numerous applications of the geosciences. He is the author of more than 150 articles in international scientific publications, more than 200 papers at conferences and 5 international books related to signal processing, data and machine learning methods. He has coordinated twelve research projects, as well as various contracts funded by the European Commission, the European Space Agency and EUMETSAT. He holds a Consolidator Grant and is a main researcher and part of the international team with a Synergy Grant, both from the European Research Council (ERC), to advance statistical learning and modelling of the terrestrial system, with innovative techniques that include understanding and causation of phenomena associated with climate change.