Winterschool 2026

17 – 23 January 2026

Part 1: Applied AI in HCI Reserach

Basics of Reinforcement Learning (Sven M.)
Building Reinforcement Learning Systems and Tools [Practical tutorial – please reach out]
How to build a Retrieval Augmented Generation (RAG) System [Practical tutorial – please reach out]
How to speed up a literature survey with GenAI (Maxi W.)
Writing papers with AI support (Hans G.)
Meeting organization, Note-taking and transcribing with GenAI (Pascal K., Steeven V.)
Image and video creation with GenAI for research (Fiona D.)
Coding and programming with GenAI support [Practical tutorial – please reach out]
HPC: How to Slurm – Cluster Training [Practical tutorial – please reach out]
Life outside Academia: Difference in Research, How to CV and Apply to Jobs (Luke H, Markus F., Sarah V.)
System Prompt Engineering (Chris L.)

How does Stable Diffusion work? [Practical tutorial – please reach out]
Setting up Stable Diffusion and fine-tuning with your images [Practical tutorial – please reach out]
How to fine-tune an LLM? [Practical tutorial – please reach out]
How to train an LLM with your own document? [Practical tutorial – please reach out]
Inside a LLM, source code, recompiling (e.g., Qwen, Qwen LLMs) [Practical tutorial – please reach out]
How do guardrails in LLMs work, looking at the source code and removing them (Katharina B.)
How does video generation work, local models for video generation [Practical tutorial – please reach out]
Beyond RAG – how to integrate your information into models (Thomas K., Jesse G.)
How to integrate sensor data models, multimodal human agent interaction (Thomas K., Ester B.)
Implementing Conversational Agents with Voice (Heiko D.)
How to set up real-time voice API (Voice to Voice) [Practical tutorial – please reach out]
Cognitive Augmentation and Manipulation with AR (Jan G.)
Expectations for a PhD (Albrecht S.)
Fun with QDA and LLMs (Pawel W.)

Organizers: