Building practical software for energy systems, data, and intelligent infrastructure.

I am interested in the intersection of electrical power engineering, software systems, and applied AI. My academic background is in Business Administration and Engineering at RWTH Aachen University, with a focus on Electrical Power Engineering. Most of the work I share here is driven by one idea: advanced systems are only valuable if they are also understandable, testable, and useful in real operating environments.

I am especially interested in cyber-physical energy systems, digital twins, middleware for operational data, and software that helps bridge the gap between technical models and practical deployment. I try to approach these areas with ambition, but also with realism. Many of the repositories here are still evolving, and I would rather describe them honestly as foundations, prototypes, or working building blocks than overstate what they can already do.

The projects below reflect the kind of systems I care about building. They are all works in progress, but each one is aimed at a concrete technical problem.

I recently revised how I describe GridOS (Under Construction) and NeuralBridge because I want their public descriptions to match their actual maturity more closely.

GridOS (under Construction) is best described, at the moment, as a lightweight DER simulation and telemetry platform for smart-grid prototyping. Its strongest areas are local experimentation, digital-twin modeling, and software structure for telemetry and control workflows. It is not yet something I would honestly describe as a complete autonomous grid operating system, and I think it is better to present it as a practical technical foundation that can grow into something stronger over time.

NeuralBridge is best described, at the moment, as a lightweight integration hub for AI workflows and external systems. The goal is to make it easier to connect tools, APIs, business systems, and operational services through a clean backend and manageable interfaces. It is still early, and I do not want to present it as a finished enterprise-grade universal middleware platform. Right now, the honest positioning is that it is a serious foundation being narrowed toward a smaller set of reliable, supported capabilities.

I care about systems that are technically sound, but also usable by real people. That usually means focusing on a few things repeatedly: clear architecture, explicit interfaces, realistic documentation, and enough testing to keep a project honest. I would rather ship a smaller system that works end-to-end than a larger one that promises too much.

Most of my development work is centered around Python, FastAPI, data tooling, and practical application design. On the interface side, I also work with React and related tooling when a project benefits from a usable frontend rather than just an API surface.