is a full professor of geomatics at the Institute of Earth Surface Dynamics, University of Lausanne. He has a PhD in theoretical plasma physics. At present, his scientific interests deal with environmental data mining, development and applications of machine learning algorithms, nonlinear time series analysis and prediction, visualization of complex high dimensional data. The main applications concern environmental risks, natural hazards, mining of socio-economic data. Prof. Kanevski is a co-author of several books on data science and more than a hundred publications on corresponding topics.

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is a professor of geophysics at the Faculty of Science, University of Zagreb. He is also a member of Croatian Academy of Science and Art. His major interests include physical processes in the sea and atmosphere-sea interaction. Thus, for example, he has recently worked on an improvement of the semi-empirical method of analysis and projection of sea level. He has also contributed to the development of some statistical methods, with one of them – partial wavelet analysis – being increasingly used not only by geoscientists but also by economists. Prof. Orlić has co-authored more than eighty refereed publications and a book on the weather and climate of the Adriatic area.

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has MSc degree in physics and the PhD degree in remote sensing. He is professor for remote sensing at the Institute of Photogrammetry and Remote Sensing of TU Wien and the head of the newly founded Department of Geodesy and Geoinformation. Furthermore, he is co-founder of the Earth Observation Data Centre for Water Resources Monitoring (EODC), acting as head of science. The main research interest lies in physical modeling and geophysical parameter retrieval from remote sensing data. He has been committee member of several international conferences.

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has been affiliated to the Norwegian Meteorological Institute (met.no) as a researcher since 1995. He became senior scientist in 1998 and was appointed as head of the “Climate data and spatial analysis” in 2011. Tveito is an experienced expert on spatiotemporal analysis of climatic variables, snow modeling, atmospheric circulation classifications, extreme value analysis and homogeneity testing. He has developed the Norwegian high resolution observation grid data set that is heavily utilized for climate assessment studies. He has a broad experience in working with scientists from other disciplines, in particular hydrology, ecology and forestry. He frequently give lectures at universities in Norway and Sweden.

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is a senior researcher at ISRIC — World Soil Information with core speciality in big data analytics and automated soil mapping. He has backgrounds in soil mapping and geo-information science. He is currently the project leader of the Global Soil Information Facilities — a suite of software tools, web-facilities and data sets (SoilGrids, soil profiles) for automated global soil mapping. He leads development of mobile phone and web apps for serving and sharing soil data from professional users to non-specialists. He is an experienced R developer (spatial and spatiotemporal data analysis); he also regularly runs training courses using Open Source Software tools via ISRIC Spring Schools and the GEOSTAT Summer schools.

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