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Growth through Mathematical Precision

When your simulations are too slow, your models aren't accurate enough, or your pipelines can't scale, standard tools run out of road. I work with companies at exactly that point, applying rigorous numerical methods and scientific computing to problems that genuinely require them.

Solver Optimisation

Your simulation works, but it's too slow for production. I apply domain decomposition and fast solver techniques to cut computation time dramatically. In one engineering project, this reduced runtimes from hours to minutes while maintaining full accuracy.

Uncertainty Quantification

When your model's output drives a decision, you need to know how much to trust it. I build statistical and probabilistic approaches that quantify model confidence, critical in regulated industries, drug discovery, and risk-sensitive applications.

Numerical Software Dev

I don’t just advise, I deliver. I design, build, and maintain production‑ready numerical software in Python, FEniCS, BEMpp, and C++, drawing on methods and standards used in published, peer‑reviewed research. Every solution is engineered to be robust, well‑tested, and maintainable, and is carefully tailored to slot into your existing infrastructure, tools, and workflows with minimal disruption.

Coupling Complex Systems

Real processes rarely fit a single model. I build frameworks that couple different mathematical methods across domains and scales, so each part of your system is solved in the most effective way, modularly and efficiently.

Removing Manual Tuning

Many numerical pipelines rely on parameters that someone has to set by hand. I design solvers that find optimal values automatically, eliminating trial-and-error and making your system reliable without expert intervention.

Engagement Models

I offer two main routes:

-direct consultancy for defined technical challenges;

- joint research partnerships for longer-term innovation, including co-developed grant applications, as UK companies may also qualify for a Knowledge Transfer Partnership, covering up to 67% of project costs through government funding.

Case studies

Design-to-simulation for manufacturing

A simulation process that previously took hours was reduced to minutes, a greater than 10x improvement in runtime, without any loss in accuracy. This was achieved by applying fast domain decomposition solvers to an isogeometric analysis workflow, exploiting the mathematical structure of the problem rather than simply adding computational power. The same methodology applies to any CAD-integrated or simulation-heavy workflow facing similar bottlenecks.

Not sure if your problem is the right fit?
Describe it to me, and I'll tell you honestly whether I can help. Get in touch →

Dr Michał Bosy

School of Computer Science and  Mathematics

Kingston University London

Penrhyn Road

KT1 2EE Kingston upon Thames

​© Michal Bosy 2026

Open to industry collaboration
and academic partnerships

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