About

I build software around optimization-heavy problems.

I am a computer science student building a profile at the intersection of backend systems, operations research, and applied optimization.

My background includes mathematical modeling, academic operations research, and backend-oriented software projects. I am especially interested in the question of how optimization models can move beyond scripts and become reliable software systems with APIs, persistence, tests, documentation, and clear architecture.

Direction

From mathematical models to usable systems

I like optimization because it turns complex operational problems into structured decisions. But I am also interested in what happens after the model exists: how it is integrated into software, how users interact with it, how results are stored, tested, explained, and improved over time.

This is why I am building depth in backend engineering. For me, backend systems are the delivery layer for optimization ideas.

Focus

What I am currently developing

Backend engineering with Java, Spring Boot, databases, testing, and CI/CD.
Operations research, solver integration, constraints, and decision models.
Applied software systems for logistics, energy, and operational domains.
Technical writing and documentation as part of engineering practice.

Stack

Tools I work with

Backend

Java, Spring Boot, REST APIs, PostgreSQL, Flyway

Optimization

Python, GurobiPy, Timefold Solver, mathematical modeling

Data analysis

Pandas, Streamlit, scikit-learn, Matplotlib

Engineering practice

Git, GitHub/GitLab, Docker, CI/CD, testing, documentation

Working style

Research. Build. Test. Optimize. Iterate.

I try to approach technical work with a mix of mathematical thinking and pragmatic engineering: understand the problem, build a clear first version, test assumptions, document trade-offs, improve the system step by step, and keep asking the critical questions.