Teaching

Teaching students to build AI systems, not just study them

Between 2019 and 2022 at the University of Passau, I taught across deep learning, information retrieval, and systems engineering, while supervising master's thesis students through their own research projects.

Courses Taught

Four courses, one throughline: applied AI

CORE AI

Deep Learning

University of Passau, 2019 – 2022

From the foundations of neural networks through CNNs, RNNs, and transformer architectures, with hands-on labs building and training models rather than just reading about them.

INFORMATION RETRIEVAL

Preference-Based Information Retrieval

University of Passau, 2019 – 2022

Ranking, relevance, and evaluation: how retrieval systems learn from preferences and feedback, covering classical IR models alongside learning-to-rank methods.

WEB & SYSTEMS

Web Science

University of Passau, 2019 – 2022

The structure and dynamics of the web as a research subject — crawling, search engines, link analysis, and the social and technical graphs that hold it together.

SYSTEMS THINKING

Complex Engineering Systems

University of Passau, 2019 – 2022

Designing and reasoning about large-scale software and AI systems, where individual components are simple but their interactions are not.

Thesis Supervision

Guiding students through their own research

Alongside teaching, I supervised master's thesis students at the University of Passau, working with them from problem formulation through experiment design and writing. Most projects sat at the intersection of NLP, information retrieval, and applied machine learning, the same areas where I supervise and mentor today.

Teaching Philosophy

Theory in service of building things

I learned to code by building, not just reading, and I teach the same way: every concept gets paired with something a student can implement, break, and fix themselves. The goal isn't to produce people who can recite an architecture diagram — it's to produce people who can debug one at 2 a.m. when it actually matters.

Looking Ahead

Courses I'd be glad to teach next

As I move toward a faculty role, I'm looking forward to extending this teaching into the areas my research has grown into since 2022.

Natural Language ProcessingInformation Retrieval & Search EnginesGenerative AI & Large Language ModelsApplied Machine LearningPatent & Innovation Analytics