Key details
Dr Mikhail Poluektov
Senior Lecturer in Materials Science and Engineering
Dr Mikhail Poluektov joined the University of Greenwich in 2025 as a Senior Lecturer in Materials Science and Engineering at the School of Computing and Mathematical Sciences. Prior to current appointment, Dr Poluektov held a Senior Research Fellow and a Research Fellow positions at the University of Warwick, Nanocomposites Research Group, and a Postdoctoral Fellow position at Uppsala University, Department of Information Technology, Division of Scientific Computing. Dr Poluektov obtained a PhD from the Eindhoven University of Technology, Mechanics of Materials Group, and MSc and BSc from St. Petersburg Polytechnic University, Institute of Applied Mathematics and Mechanics.
His research belongs to the area of computational and applied mathematics covering a large range of models and methods. In particular, his main research focuses on mathematical theory underpinning the description of materials with coupled phenomena (e.g. chemo-mechanics, magneto-mechanics). His recent developments cover fictitious-domain and multiscale methods for non-linear partial differential equations describing phase transitions and multi-physics of materials. Dr Poluektov also works on novel machine-learning models and methods.
Responsibilities within the university
- Research within M34Impact programme.
- Supervision of PhD students.
- Supervision of 3rd-year and 4th-year students at the School of Computing and Mathematical Sciences.
- Contribution to the development of a new MSc programme at the School.
Research / Scholarly interests
- Multiscale computational methods for materials modelling (atomistic-to-continuum coupling, mesoscopic-scale models materials’ microstructures, computational homogenisation, coarse-graining, mean-field methods, modelling of structure-properties relationship, application to polymers)
- Continuum mechanics and thermodynamics theory, multi-physics coupling (materials demonstrating chemo-mechanical and magneto-mechanical behaviour, application to energy-storage materials, application to shape-memory alloys)
- Numerical analysis (fictitious-domain methods, cut-finite-element method for non-linear partial differential equations, multiscale methods)
- Computational solid mechanics (modelling of time-dependent interfaces, fracture and contact, phase-field methods)
- Modelling of phase transitions in solids, mechanics-diffusion-reaction models (stability analysis of phase boundaries and chemical-reaction fronts, localisation of stress-affected chemical reactions)
- Magnetic materials modelling (interaction of domain walls and skyrmions with crystallographic defects, coupling of atomistic spin dynamics to continuum micromagnetics)
- Machine learning (Kolmogorov-Arnold networks, discrete Urysohn operators)