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Personal profile

Research interests

I have founded and lead GeoDataScience group at the Instutte of GeoEnergyEngineering. My research interests lie broadly across spatial statistics, machine learning and uncertainty.

In particular my research is focused on:

  • uncertainty quantification in prediction modelling
  • inverse modelling for history matching
  • stochastic optimisation
  • Bayesian inference.
  • advance geostatistical techniques, such as multi-points statistics, and the problem of integration of relevant domain knowledge and data into statistical models.
  • machine learning and data mining approaches for reservoir modelling and uncertainty quantification. 

I lecture geostatistics to MSc students and also at IPE summer schools and EAGE educational days. I am a co-author of over 100 publications, including books: Challenges and Solutions in Stochastic Reservoir Modelling with D Arnold (EAGE 2018), Geostatistics: Theory and Practice  with E. Savelieva (Nauka, 2010, in Russian), Advanced Mapping of Environmental Data – Geostatistics, Machine Learning and Bayesian Maximum Entropy (Wiley, 2008).

Graduated PhD students supervised:


  • University of Lausanne, Switzerland: Prof M. Kanevski, Prof. I. Lunati, L. Josset, Prof. M. Maignan
  • CERENA, Institute Superior Technico, Lisbon, Portugal: Prof. A. Soares, Dr L. Azevedo,Dr. S. Focaccia, M.-H. Caeiero.
  • Gubkin Oil and Gas University (Moscow, Russia)
  • Tomsk Polytechnic University, Russia.
  • Dr. E. Savelieva (Nuclear Safety Institute, Moscow, Russia)
  • Prof. J. Caers, Stanford University, USA
  • Prof. George Christakos
  • Marc Serre, University of Chapel Hill, USA


2003: I joined Heriot-Watt University and was later promoted to Research Fellow and then to a Lecturer.

2000-2002: Post-doc on population dynamics modelling, University of St Andrews, Mathematical Institute,.

1998: PhD degree in physics and mathematics from Russian Academy of Sciences (Nuclear Safety Institute)

Thesis on radioactive pollution modelling with geostatistics and artificial neural network.

1994: My first degree is in physics from Moscow State University. Thesis on atmospheric pollution transport modelling.

Editorial roles:
2011-2020: Computers and Geosciences, Associate Editor
2014-2015: Computers and Geosciences, Guest Editor for a special issue "Statistical learning in geoscience modelling: Novel algorithms and challenging case studies", Volume 85, Part B

2018-2019: Mathematical Geosciences, Guest editor for a special issue “Data Science for Geoscience”

2021: Energies MDPI Open Access Journal, Guest Editor for a SI "Data Science in Reservoir Modelling Workflows"

I am a member of the International Association for Mathematical Geosciences (IAMG) and European Association of Geoscientists and Engineers (EAGE).

I was a convener of the Machine learning session at Annual IAMG meetings in 2009 and 2013 and also a member of the scientific committees for a number of geostatistical and geosciences conferences.


  • QC Physics
  • uncertainty
  • machine learning
  • statistics
  • geostatistics
  • optimisation
  • Bayesian
  • prediction modelling
  • petroleum
  • geoscience
  • environmental mapping
  • inverse modelling
  • predictions


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