Dr Andrei Shvarts
- Lecturer (Infrastructure & Environment)
telephone:
01413305662
email:
Andrei.Shvarts@glasgow.ac.uk
79-85 Oakfield Avenue, Rankine Building, Glasgow, Scotland, United Kingdom, G12 8LT
Biography
Andrei earned his BSc (2012) and MSc (2014) degrees with distinction in Applied Mathematics and Computer Science from St. Petersburg Polytechnic University (alma mater of Boris Galerkin). During his master studies, he completed two internships with global industrial leaders, applying finite-element approaches to real-world engineering challanges at General Motors R&D (Michigan, US) and Airbus R&D (Toulouse, France).
Andrei pursued doctoral studies at École des Mines de Paris (MINES ParisTech – PSL University) in collaboration with Safran Tech, completing his PhD thesis in 2019. His doctoral research focused on developing a coupled numerical framework to simulate fluid transport across contact interfaces between rough surfaces - a challange relevant for applications in lubrication and sealing, including nuclear industry problems. The outstanding quality of his work was recognised with two national PhD awards: from the French Computational Structural Mechanics Association (affiliated with ECCOMAS) and from the French Mechanical Association for the best dissertation in tribology.
Andrei joined the University of Glasgow as a postdoctoral researcher in 2019, contributing to the modelling of fracture in irradiated graphite bricks in collaboration with EDF Energy. His work focused on enhancing the capabilities of MoFEM — an open-source, parallel finite element library developed at GCEC — to model the complex interaction between propagating cracks and contact interfaces in nuclear reactor's core. His postdoctral research was recognised with the prize for the best presentation at the UKACM conference (2019).
Since 2021, Andrei has held the position of Lecturer in Computational Mechanics at GCEC, where he continues to advance cutting-edge research in the field. In particular, he applies his expertise in applied mathematics and numerical modelling to lead a range of research projects across civil, mechanical, electrical, and biomedical engineering. Andrei is also a Core Developer of MoFEM and a member of its Scientific Management Board.
Research interests
My interests are centred on developing novel, disruptive approaches to numerical modelling in engineering and applied physics, with a strong emphasis on industrial applications. I am one of core developers of MoFEM, an advanced open-source finite-element library with HPC capabilities for solving multi-field, multi-physics and multi-scale problems. In particular, my work focuses on the development and implementation of mixed finite element methods, enabling automated simulation workflows through error-driven adaptive refinement and delivering excellent solver scalability, including GPU parallesation.
Since my appointment as a Lecturer, I have been building a research group dedicated to developing cutting-edge computational tools that support collaborations with colleagues across related disciplines and industry partners. Currently, my research focuses on the following key directions:
- Numerical simulation of triboelectric nanogenerators (TENG). TENG devices convert mechanical into electrical energy, offering autonomous clean power. Accurate modelling requires multi-scale, multi-physics simulations capturing statistically representative surface roughness. Using MoFEM, we aim to accelerate TENG design, optimisation, and prototyping. Collaboration: MMRG.
- Data-driven (DD) computational mechanics. This approach bypasses constitutive model fitting by directly integrating experimental data into finite element simulations, while satisfying conservation laws and boundary conditions using FEM. DD aproach is particularly powerful for complex behaviours such as fracture of heterogeneous materials, unsaturated flow, and granular rheology. Collaboration: EDF Energy.
- Modelling of nanoelectronic devices. Efficient chip packaging relies on detailed simulations of electron transport, heat transfer, and mechanical stress in highly heterogeneous solids. Mixed finite element methods permit to capture low-regularity solitions and yield solver-friendly matrix structures, enabling highly scalable multi-physics models. Collaboration: DeepNano research group.
- Simulation-augmented atomic force microscopy (AFM). AFM nanoindentation is enhanced by coupling with finite element analysis, capturing material heterogeneity and nonlinear response. This approach improves measurement precision and deepens understanding of cellular and tissue biomechanics. Collaboration: CeMi.
- Advanced simulation capabilities for hyperelastic and elastoplastic materials. We develop high-order finite element methods with GPU acceleration, adaptive refinement, and uncertainty quantification to tackle complex nonlinear problems involving large deformations, contact, buckling, and imperfections. Collaboration: Freudenberg Group.
- Scalable solvers for solid mechanics. This project reformulates finite element algorithms with mixed and hybrid (multifield) methods to fully exploit GPU architectures, enabling efficient, scalable simulations of heterogeneous materials, finite elasticity, plasticity, fracture, and contact. Collaboration: Siemens.
- High-Performance Modelling of the Full Spine. We develop advanced finite element models of intervertebral disc biomechanics to investigate degeneration linked to lower back pain. Mixed formulations, GPU acceleration, and clinical data integration enable efficient, patient-specific simulations. Collaboration: BMMB, Universitat Pompeu Fabra (Barcelona).
Supervision
All interested candidates are invited to get in contact with me to discuss the project and scholarship opportunities.
Currently I supervise the following PhD students:
- Esmail, Mohamed: Advanced Simulation Capabilities for Reinforced Tubular Structures Under Complex Loading Conditions
- Gao, Yingjia: Simulations and modelling heterogeneous materials from an electronic device packaging prospective
- Johnson, Cai: Stem cell/niche biomechanics in intestinal health and disease
- Cerdán, Heriberto (Heri) Busquier: Data-driven computational modelling for assessing structural integrity of civil nuclear reactors
- Shevchenko, Bohdan: Scalable solvers for solid mechanics problems for GPGPUs
- Sierra Fisher, Liliana Anoushka: High-Performance Simulations of the Full Spine Using a Novel Poromechanics Model for Intervertebral Discs
- Wang, Zifeng: A Smarter Way to Model Low-Power Memory Devices
- Sanglap, MD Tanzib Ehsan
Transient simulation of triboelectric nanogenerators considering surface roughness
Completed PhD Students:
-
Adriana Kuliková (2025): Data-Driven Weaker Mixed Formulation for Diffusion Problems
Teaching
I currently teach the following courses:
I supervise undergraduate and postgraduate students in the following projects:
Previously, I have also taught:
