Prof Vasily Demyanov of Institute of Petroleum Engineering, Heriot-Watt University (Edinburgh), lectures geostatistics and leads industry and government funded research in Geo Data Science and uncertainty quantification for reservoir prediction modelling.  He has over 20 years of experience in geostatistics and has published over 100 publications. Vasily has co-authored a number books: Challenges and Solutions in Stochastic Reservoir Modelling – Geostatistics, Machine Learning, and Uncertainty Predictions with EAGE (2018); Geostatistics: Theory and Practice (Nauka, 2010, in Russian). Vasily Demyanov is an Associate editor for Computers and Geosciences Elsevier journal and a guest editor for Mathematical Geosciences Springer Journal special issue on Data Science in Geoscience due in 2019. Vasily Demyanov is an Associate editor for Computers and Geosciences Elsevier journal. 

Vasily’s research interests lie broadly across spatial statistics, machine learning and uncertainty. In particular his research is focused on uncertainty quantification in prediction modelling, inverse modelling for history matching, stochastic optimisation, Bayesian inference, and the problem of integration of reservoir knowledge and relevant data into statistical modelling workflows with machine learning and data analytics approaches. 

Vasily Demyanov obtained the first degree in physics from Moscow State University (1994) and a PhD in physics and mathematics from Russian Academy of Sciences (1998) with a thesis on radioactive pollution modelling with geostatistics and artificial neural networks. Prior to joining Heriot-Watt in 2003 he worked with the University of St. Andrews (2000-2002) and Nuclear Safety Institute, Moscow (1994-2000).