Hi, I'm Matthew 👋

M.Sc. student in Applied Informatics in Natural Sciences at FJFI (Faculty of Nuclear Sciences and Physical Engineering), ČVUT (Czech Technical University) in Prague.

My interests sit at the intersection of high-performance computing, numerical methods, quantitative finance, machine learning, and modern systems programming. I enjoy building software that pairs strong theoretical foundations with practical performance.

Areas of interest

Modern C++ & Rust HPC Scientific Computing Numerical Methods & Optimization Quantitative Finance Machine Learning Parallel Programming Visualization & GUI Development

Languages & technologies

Languages
C++HPC C++Rust PythonC#
Domains
Scientific ComputingOptimization Machine LearningQuantitative Finance Numerical Linear AlgebraPerformance Engineering
Frameworks & tools
QtFastAPIReact CUDA (learning)GitLinux
Practices
CI/CD (GitHub Actions)Unit Testing CodecovStatic Analysis

Research

I contribute to TNL (Template Numerical Library), where my graduate research focuses on implementing an Active-Set Quadratic Programming solver in modern C++. The project extends TNL with efficient optimization algorithms for scientific-computing applications.

MarketPulse AI also doubles as research infrastructure for an upcoming paper comparing Prophet vs. LSTM+Prophet hybrid models for financial time-series forecasting.

Featured projects

Current focus

High-performance numerical algorithms Optimization methods Scientific software engineering Quant finance research ML for financial time series Modern C++ & Rust ecosystems

Philosophy

I enjoy building software where mathematics, algorithms, and performance matter. Whether it's numerical solvers, financial models, visualization tools, or machine learning systems, I'm interested in producing software that is both scientifically rigorous and practical.

I use AI-assisted development tools (Claude Code, GitHub Copilot) to accelerate implementation while maintaining rigorous engineering practices, testing, and code review.