- PHD External Examiner University of Lille 1 (France)
- External Examiner
more professional activities
- 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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