- modules: pixels, geometry, classical ML, GANs, VAEs, Diffusion Models. /post test: 15.1% to 50.5% (Cohen's d = 1.615, p = .008). l-format pedagogy: hands-on discovery and conceptual deep-dives. chDesigner integration for creative coding workflows.
Open-source AI curriculum (15 modules) built as a Master's thesis, guiding learners from pixel manipulation to GANs, VAEs, and Diffusion Models. A user study with 9 participants showed knowledge scores rise from 15.1% to 50.5% (Cohen's d = 1.615, p = .008).
- 〔0〕 Python
- 〔1〕 NumPy
- 〔2〕 Jupyter
- 〔3〕 PyTorch
- 〔4〕 TensorFlow
- 〔5〕 scikit-learn
- 〔6〕 OpenCV
- 〔7〕 TouchDesigner
- lvable boid flocking (separation, alignment, cohesion). dator black holes with gravitational lensing. rnament selection and uniform crossover across generations. rum sensing: density-triggered collective defense.
Real-time generative art installation combining boid flocking with an evolutionary algorithm — stars evade predator black holes and pass survival traits across generations. Exhibited at the Pixels2GenAI exhibition, Berlin (2026).
- 〔0〕 Python
- 〔1〕 Pygame
- 〔2〕 NumPy
- sarum agents sense, rotate, and deposit pheromone trails. bian synapses form on agent co-activation. vitals drive color, bloom, and step size. L compute shaders, 60 FPS at 1920×1080.
Real-time generative artwork where live GPU vitals — temperature, clock, utilization, power — sculpt a mycelial Physarum simulation coupled to a Hebbian neural network. Up to 200,000 agents render at ~60 FPS via GLSL compute shaders.
- 〔0〕 Python
- 〔1〕 OpenGL
- 〔2〕 GLSL
- 〔3〕 CUDA
- 〔4〕 Pygame
- 〔5〕 SciPy
- trolNet conditioned on Canny edges and MediaPipe landmarks. M with linear, cosine, and quadratic noise schedules. nc generation pipeline keeping display at 30 FPS. ional sound reactivity and ambient audio synthesis.
Interactive art installation where visitors watch themselves dissolve into noise and crystallize as anime artwork via Stable Diffusion and ControlNet. Exhibited at IT Studio Academis, Berlin (2026), with async generation at ~3s/frame and live display at 30 FPS.
- 〔0〕 Python
- 〔1〕 Stable Diffusion
- 〔2〕 ControlNet
- 〔3〕 MediaPipe
- 〔4〕 OpenCV