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

In particular my research is focused on:

• Use AI to discover patterns in reservoir data and improve our understanding of the subsurface for better management of Earth resourcers;
• Uncertainty quantification in prediction modelling;
• Unverse modelling for history matching and Bayesian inference;
• stochastic optimisation
• data science and geostatistical methods for 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:

• Linah Mohammed, PhD 2011: Novel sampling techniques for reservoir history matching optimisation and uncertainty quantification in flow prediction (2^nd supervisor);
• Yasin Hajizadeh, PhD 2011: Population-based algorithms for improved history matching and uncertainty quantification of Petroleum reservoirs, 2^nd place - SPE international student paper contest 2010,  1^st place - SPE student paper contest, European region 2009,  (2^nd supervisor);
• Temistocles Rojas, PhD 2014: Controlling Realism and Uncertainty in Reservoir Models using Intelligent Sedimentological Prior Information  (1^st supervisor);
• Junko Hutahaean, PhD 2017, Multi-Objective Methods for History Matching, Uncertainty Prediction and Optimisation in Reservoir Modelling, 1^st place - SPE student paper contest, European region 2013,  (1^st supervisor);
• Aklexandra Kuznetsova, PhD 2017, Heirarchical geological realism in history matching for reliable reservoir uncertainty predictions, 2^nd place - SPE International student paper contest 2016,  1^st place - SPE student paper contest, European region 2016,  (1^st supervisor);
• Behzad Nezhad Karim Nobakht, PhD 2018, Modelling discrepancy in Bayesian calibration of reservoir models, (2^nd supervisor).
• Dr Bastian Steffens, PhD 2022: Integrating geological uncertainty and dynamic data into modelling procedures for fractured reservoirs,
• Dr Gleb Shishaev, 2024: History Matching and Uncertainty Quantification of Reservoir Performance with Generative Deep Learning and Graph Convolutions

• 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.