Janik Vollenweider
Applied AI & Reinforcement Learning
Research Associate · FHNW · Cybernetic Learning Systems Research Unit
I contribute to the development of AI systems that support human decision-making in complex, safety-relevant environments. My focus lies in applied reinforcement learning and decision intelligence, particularly in aviation and operational contexts.
From theory to practice — watch my research come alive
My Research • Live & Interactive
See Reinforcement Learning in Action
This isn't just a demo — it's a real-time demonstration of the AI research I develop for safety-critical systems. Watch skills emerge as a neural network learns to land a spacecraft, starting from zero knowledge.
The Deep Q-Network training right now in your browser mirrors the same principles I apply to aviation decision-support systems. Every successful landing you witness represents thousands of learning iterations, just like the AI systems I design for real-world deployment.
Live Training Metrics
Watch the agent learn to land in real-time using Deep Q-Learning. Training happens entirely in your browser using TensorFlow.js.
Collaboration
From Research to Reality
I enjoy working in collaborative research and industry settings to move reinforcement learning from experimental setups to real-world applications. If you’re interested in applied AI or decision intelligence projects, I’d be glad to connect.