CREATIVE TECHNOLOGIST · COLOGNE

I build things people can play with.

Interactive installations, physical games, and unexpected effects. Made with code, electronics, and a lot of hands-on building.

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Selected projects

Code meets the physical world.

More things I make

Latest physical projects

  • The Confessional

    A confessional box at Walden Festival 2026 where visitors confess their sins to a local AI priest, who grants absolution - and forwards the sins, anonymized and retold in an angel’s voice, to the Holy Toilet.

  • The Palapian's Spaceship

    An interactive, networked spaceship you can actually board: players complete (or sabotage) missions across a dozen physical interfaces - buttons, joysticks, LED boards, sensors, etc - to either launch the ship or doom it, with everything driven by a Python/ESP/Unity stack. It’s modular, auto-resets regularly, and scales to festival crowds without manual babysitting.

  • Tux-Kart with Real-Life Powerups

    Festival Installation where two people play OSS-Mariokart, but instead of Koopas the in-game items squirt water or fog at the opponent or hit with the Poolnudelschlagapparat.

  • CAD and 3D-Printing

    Having learned my ways on Theseus’ Anet A8 and now running a boringly reliable Bambu P1S, I use 3D printing and self-taught CAD as basic infrastructure for most of my hardware projects, some of which are listed here.

👉 More physical projects

Latest digital projects

  • Paper-Code Matching with Repository-Level Code Embeddings

    During my discontinued PhD at DLR, I developed and trained a graph neural network to combine code embeddings into repository-level representations and align them with scientific publications. Preliminary evaluation showed a promising improvement over pooling baselines, as a first step towards finding related implementations and their underlying assumptions across research fields.

  • Automatic Meal Recognition

    An automated self-checkout system that recognizes meals on canteen trays using machine learning.

  • Siddata Study Assistant

    A Stud.IP-Plugin to recommend relevant university courses using machine learning

  • Masterthesis: Explainable Course Recommendation

    For this thesis, I created a Conceptual Space from Course Descriptions for explainable Recommendation, in a highly performant pipeline on the university-grid.

👉 More digital projects

Have something in mind?

Let's talk about installations, playful interfaces, or working together.

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Chris Stenkamp · Cologne