Dr Michal Bosy

I am a supervisor of postgraduate and undergraduate students working on their dissertation projects in Data Analysis, Numerical Methods and Computational Mathematics.

I am or was (depending on the term) a teacher of:

• FX3002 Foundation Project-Based Learning module
• CI4105: Programming 1 - Think like a programmer module
• CI4450 Professional Environments module
• MA4510 Problem Solving and Computational Mathematics module
• MA4700 Mathematics of AI module (Module Leader)
• EG4012 Engineering Mathematics and Computing module
• CI5250 Computing Systems module
• CI5450: Professional Environments 2 module
• MA5500 Application of Calculus and Linear Systems module (Module Leader)
• MA6530 Optimisation Techniques and Applications module
• MA6910 Individual Project module
• CI7000 Project Dissertation module
• CI7340: Applied Data Programming module
• CI7522 Ethics and Regulation of Artificial Intelligence module (Module Leader)

Qualifications

• Fellow of Higher Education Academy

Courses taught

• Computer Science and Artificial Intelligence BSc (Hons)
• Computer Science BSc (Hons)
• Artificial Intelligence MSc
• Data Science MSc

As a mathematician and computer scientist, I try to understand the world by

• Modelling real-life problems using differential equations.
• Building efficient solvers for large linear systems.
• Developing numerical software.
• Researching machine learning approaches for uncertainty.

My research interests are focused on the design and analysis of coupling methods for partial differential equations. These methods arise because of considering multi-physics problems, non-conforming methods or using domain decomposition methods. The applications that I have studied include such fields of science and engineering as fluid dynamics, continuum mechanics, wave propagation and biomolecular physics.  

My theoretical investigations include the design of well-posed discrete problems and a priori error analysis for Galerkin finite element methods using continuous and discontinuous approximation spaces. 

My computational studies include the design of efficient iterative solvers using domain decomposition methods that allow taking advantage of modern parallel architectures.

Qualifications

• Numerical Analysis
• Computational Mathematics
• Mathematical Modelling

Specialisms

• Finite and boundary element methods
• Domain Decomposition methods
• Partial Differential Equations
• Multi-physics problems
• Coupling methods

University responsibilities

• Organiser of the Faculty of Engineering, Computing and the Environment Seminar