Andrei is a Lecturer at the James Watt School of Engineering, where he leads interdisciplinary research projects applying computational methods across civil, mechanical, electrical, and biomedical engineering, and brings this expertise into research-led teaching. He is also an academic member of the Glasgow Computational Engineering Centre, where he organises the internal and external seminar series and leads the reading group on advanced topics in computational engineering, such as functional analysis.

Andrei is a core developer of MoFEM and a member of its Scientific Management Board. MoFEM is an open-source finite element library that incorporates modern approximation approaches and high-performance computing tools for industrial engineering applications. Recently, he co-founded Mesh-Oriented Solutions Ltd (MOS), a University of Glasgow spin-out that leverages MoFEM to deliver tailored, automated simulation pipelines for a wide range of industrial partners. Drawing on his experience in leading research projects, he serves as Scientific Director of MOS.

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 to model the complex interaction between propagating cracks and contact interfaces in the nuclear reactor core. His postdoctoral research was recognised with the prize for best presentation at the UKACM Conference in 2019. 

Andrei pursued doctoral studies at École des Mines de Paris (MINES Paris – PSL University) in collaboration with Safran Tech, completing his PhD thesis in 2019. His research focused on developing a coupled numerical framework to simulate fluid transport across contact interfaces between rough surfaces, with applications in lubrication, sealing, and the nuclear industry. The 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 of the year.

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’s studies, he completed two internships with global industrial leaders, applying finite element approaches to real-world engineering challenges at General Motors R&D in Michigan, US, and Airbus R&D in Toulouse, France.

My research interests centre on developing novel, disruptive computational methods for numerical modelling in engineering and applied physics, with a strong emphasis on industrial applications. In particular, I co-lead the development and application of MoFEM, an advanced open-source finite element library with high-performance computing capabilities for solving multifield, multiphysics, and multiscale problems. In recent years, my research has focused on mixed finite element methods that enable automated simulation workflows through error-driven adaptive refinement and deliver excellent solver scalability, including GPU parallelisation.

As a Lecturer, I am building a research group focused on developing advanced computational tools for interdisciplinary academic collaboration and industrial partnerships. My current research focuses on the following areas:

• Numerical simulation of triboelectric nanogenerators (TENG). TENG devices convert mechanical energy into electrical energy, offering a route to autonomous clean power. Accurate modelling requires multiscale, multiphysics simulations that capture 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 enforcing conservation laws and boundary conditions using FEM. DD aproach is particularly powerful for complex behaviours such as fracture in heterogeneous materials, unsaturated flow, and granular rheology. Collaboration: EDF Energy.
• Modelling of nanoelectronic devices. Efficient chip design and packaging rely on detailed simulations of electron transport, heat transfer, and mechanical stress in highly heterogeneous structures. Mixed finite element methods make it possible to capture low-regularity solutions and yield solver-friendly matrix structures, enabling highly scalable multi-physics models. Collaboration: DeepNano research group.
• Simulation-augmented atomic force microscopy (AFM). AFM nanoindentation can be enhanced by coupling experiments with finite element analysis to capture 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 associated with lower back pain. Mixed formulations, GPU acceleration, and clinical data integration enable efficient, patient-specific simulations. Collaboration: BMMB, Universitat Pompeu Fabra (Barcelona).

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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
• Wang, Zifeng: A Smarter Way to Model Low-Power Memory Devices

• Manrique Aguirre, Cleison Armando
  GPU-accelerated simulation capabilities for lifetime estimation of large connector seals
• Sanglap, MD Tanzib Ehsan
  Transient simulation of triboelectric nanogenerators considering surface roughness
• Sierra Fisher, Liliana Anoushka
  High-Performance Simulations of the Full Spine Using a Novel Poromechanics Model for Intervertebral Discs

Completed PhD Students:

• Adriana Kuliková (2025): Data-Driven Weaker Mixed Formulation for Diffusion Problems

I am the course coordinator and lecturer for:

• Statics 1 (ENG1065)

I also teach the following courses:

• Structural Mechanics 3 (ENG3047)
• Structures in Action M (ENG5088)

I supervise undergraduate and postgraduate students in the following projects:

• MSc project (ENG5059P)
• Individual project 5 (ENG5041P)
• Individual project 4 (ENG4110P)

Previously, I have also taught:

• Finite Element Analysis 4/M (ENG4025/ENG5294)
• Mechanics of Structures 2B (ENG2082)
• Biosensors and Diagnostics 4/M (ENG4036/ENG5288)