The technical line that runs through the three sections on this page.
This is where the recurring thread comes together: building, tinkering, structuring, and eventually creating something that is not just interesting, but actually works in real life.
By the age of three I was already hammering nails into a plank. My grandmother held the nail while I handled the hammer, which in hindsight was a remarkable amount of trust. I must have hit the target often enough, because from there things continued quite steadily with a workbench, craft projects, competitions, and later increasingly complex technical topics.
I spent a lot of my childhood building, tinkering, and trying things out. In fourth grade I built a rocket as stage scenery for a theatre play, and for Explore Science we built a marble run, still completely without programming or microcontrollers, but with plenty of circuits, sensors, and exactly the kind of tinkering that still appeals to me today. Later there were more projects, competitions, and formats such as First Lego League, first as a participant and now even as a juror.
Technology and design never really left me after that and eventually became a natural part of my professional path as well. I studied industrial engineering and specialised in data science during my master's degree. Part of that work focused on how large language models can be used for synthetic training data in healthcare. Today I work as a Data & Analytics Engineer in a pharmaceutical environment.
What interests me there is not just the technology itself, but the question of how to solve concrete problems with it in a sensible way. At work that means solutions that actually improve something. In private it often turns into surprisingly elaborate answers to problems that, outside my own head, probably nobody else had.
That is exactly what leads into the three sections below: AI as a thinking and working tool, 3D printing for physical parts, and smart home for systems that have to hold up in everyday life.
What interests me about AI is not only what becomes faster, but what becomes possible at all. It gets genuinely interesting where a solid technical foundation meets new tools: in my master's thesis, in programming, in writing, and anywhere an idea can turn into a clean solution much faster.
An overview of my master's thesis on how large language models such as GPT-4 can augment synthetic training data for machine-learning applications in healthcare.
A coming article about how I actually used AI while building this website, where it was extremely strong, and where you still have to think, structure, and decide in a very classical way.
The 3D-printing side is not an STL shelf, but a collection of concrete solutions. What interests me are the projects where design, iteration, and sometimes small helper tools come together until a part actually works in everyday use.
A gloriously nerdy project where official aircraft geometry, CAD abstraction, a small helper application in the background, and a highly unreasonable amount of baking all ended up in the same place.
A very concrete interface problem from photography practice: a custom adapter that lets a Haida 100 mm filter system sit properly on the NIKKOR Z 14-24 mm without ignoring the lens geometry.
This is where you notice fastest whether technology merely sounds clever or actually holds up. I am not interested in gimmicks, but in systems that do not become annoying at night, react reliably during the day, and stay stable even when sensors, guests, or edge cases get in the way.
How I derive light from outdoor brightness, cloud cover, blinds, and sleep state instead of constantly reaching for switches or voice assistants.
As soon as music, rooms, and presence start working together cleanly, you notice whether a smart home really feels coherent. Sonos is a good example and deserves its own piece later.