Professor Maxim Fedorov



Multi-solvent models for solvation free energy predictions using 3D-RISM hydration thermodynamic descriptors
Subramanian Vigneshwari, Ratkova Ekaterina, Palmer David S, Engkvist Ola, Fedorov Maxim V, Llinas Antonio
Journal of Chemical Information and Modeling Vol 60, pp. 2977-2988 (2020)
GraphDelta : MPNN scoring function for the affinity prediction of protein-ligand complexes
Karlov Dmitry S, Sosnin Sergey, Fedorov Maxim V, Popov Petr
ACS Omega Vol 5, pp. 5150-5159 (2020)
Mechanisms of surface charge modification of carbonates in aqueous electrolyte solutions
Derkani Maryam H, Fletcher Ashleigh J, Fedorov Maxim, Abdallah Wael, Sauerer Bastian, Anderson James, Zhang Zhenyu J
Colloids and Interfaces Vol 3 (2019)
A survey of multi-task learning methods in chemoinformatics
Sosnin Sergey, Vashurina Mariia, Withnall Michael, Karpov Pavel, Fedorov Maxim, Tetko Igor V
Molecular Informatics (2018)
NaRIBaS-a scripting framework for computational modeling of nanomaterials and room temperature ionic liquids in bulk and slab
Nerut Eva Roos, Karu Karl, Voroshylova Iuliia V, Kirchner Kathleen, Kirchner Tom, Fedorov Maxim V, Ivaništšev Vladislav B
Computation Vol 6 (2018)
3D matters! 3D-RISM and 3D convolutional neural network for accurate bioaccumulation prediction
Sosnin Sergey, Misin Maksim, Palmer David S, Fedorov Maxim V
Journal of Physics: Condensed Matter Vol 30 (2018)

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Professional activities

PHD External Examiner University of Lille 1 (France)
External Examiner

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Understanding the colloidal interactions at rock/oil interface via combination of direct measurements and large-scale molecular simulation
Zhang, Zhenyu (Principal Investigator) Fedorov, Maxim (Co-investigator)
01-Jan-2015 - 30-Jan-2018
Schlumberger grant "Experimental and theoretical approaches for interfacial properties"
Fedorov, Maxim (Principal Investigator) Zhang, Zhenyu (Co-investigator)
15-Jan-2014 - 31-Jan-2014
SME Engagement Springboard for Archie-West
Mulheran, Paul (Principal Investigator) Fedorov, Maxim (Co-investigator)
21-Jan-2014 - 20-Jan-2015
Large-scale simulations of petrophysically relevant aqueous brine solutions
Fedorov, Maxim (Principal Investigator)
01-Jan-2013 - 30-Jan-2015
Using big data analytics and genetic algorithms to predict street crime
Bellingham, Richard (Principal Investigator) Andonovic, Ivan (Co-investigator) Fedorov, Maxim (Co-investigator) Quigley, John (Co-investigator) Rogerson, Robert (Co-investigator) Tata, Cyrus (Co-investigator)
Street crime and fear of street crime have significant adverse impacts on individual lives, the use and regeneration of urban areas, the ability to attract businesses and investment, the price of property, and the ability of citizens to live full and creative lives. Previous studies have examined the relationships between a range of social, economic and situational factors and levels and predictability of crime using a range of techniques. However the impact of altering these factors (where they can be influenced), and how such measures might be combined with other potential crime reduction measures are not fully understood.

This research aims to achieve new insights into the pattern of crime in cities using big data analytics to analyse the relationships between multiple datasets and levels of crime, and use genetic algorithms to derive innovative optimised strategies that result in lower levels of street crime alongside balancing other objectives - such as lower service costs (eg from improved design of street lighting, and policing patterns), lower carbon emissions, and improved public confidence and acceptance. These strategies will be tested through using the city as a living lab, drawing on Glasgow's Technology Strategy Board (TSB) City Demonstrator role.
01-Jan-2013 - 30-Jan-2015
Investigating the accuracy of sublimation free energy prediction by ab initio and semi-empirical methods.
Palmer, David (Principal Investigator) Fedorov, Maxim (Principal Investigator) Mitchell, John (Academic) van Mourik, Tanja (Academic) McDonagh, James (Researcher)
This project aims to investigate how accurately sublimation free energy (ΔGsub) of small to medium sized organic molecules can be predicted by theoretical methods. We plan to use ab initio calculations from CASTEP and CRYSTAL09 to compare with lattice simulations, the latter performed in-house. Our motivation for the project is to improve our ability to predict solution free energy (ΔGsolv) (and solubility) from a thermodynamic cycle.

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