Mikhail Kanevski is a Professor of geomatics at IDYST Institute, University of Lausanne. He has a MS degree in physics and a PhD in theoretical plasma physics from Moscow State University. His current scientific interests cover a wide range of topics: geographical information science, environmental modelling, spatial statistics, time series forecasting, machine learning and environmental data mining. At present, the major applications deal with natural hazards, environmental pollution and renewable energy analyses and assessments. Prof. Kanevski is a co-author of several books on geostatistics and machine learning applied to environmental sciences, and he published many refereed papers on different fundamental and applied research problems.
In collaboration with Prof. Michel Maignan (University of Lausanne), he published in 2004 a book entitled “Analysis and modelling of spatial environmental data”, along with the Geostat Office software. The book and software cover a wide range of topics on spatial data modelling, introducing geostatistics and machine learning algorithms in the environmental sciences. In 2008 Prof. Kanevski edited a book, “Advanced Mapping of Spatial Data. Geostatistics, Machine learning, Maximum Bayesian Entropy”, prepared by an international team of co-authors and published by iSTE and Wiley. In 2009, a new book entitled “Machine Learning for Spatial Environmental Data. Theory, Applications and Software” was published by EPFL Press and CRC Press. The last book provides data and a variety of professional software modules – Machine Learning Office, covering major machine learning algorithms and their applications for environmental data. These books are the basis for the MS courses “Geostatistics and GIS” and “Environmental Data Mining”.
The models developed and adapted by the group of Prof. Kanevski were successfully applied to geo-, environmental and socio-economic spatio-temporal data analyses. The fundamental scientific research of Prof. Kanevski was supported by many SNSF grants. At present Prof. Kanevski is a co-PI (collaboration with EPFL) of the PNR75 “Big Data” project “Hybrid renewable energy potential for the built environment using big data: forecasting and uncertainty estimation”. Prof. Kanevski was a scientific (co)advisor of more than 20 successfully defended PhD theses and 45 master projects on different topics. Prof. Kanevski is a member of editorial advisory board of the international journal “Computers and Geosciences”.