Data Science Group @ Heidelberg University
Welcome to the Data Science Research Group at Heidelberg University. Our research focuses on the management, processing, and analysis of complex data, ranging from scientific datasets to large-scale text corpora.
We work at the intersection of data science, natural language processing (NLP), information retrieval, machine learning, and generative AI. Our goal is to develop methods and techniques for practical, user-centered tools that support chatbots, question-answering systems, conversational AI, and transparent reasoning. Much of our published work is interdisciplinary and connects to fields such as medicine, mental health, law, politics, and education.
In addition to our research, we offer courses, seminars, and software practicals at both introductory and advanced levels. For current and past offerings, please see our teaching page. Students interested in pursuing a Bachelor’s or Master’s thesis are encouraged to visit this page first. If you are interested in an introductory or advanced research project, please feel free to get in touch. Open student research projects are typically presented at the beginning of lectures each semester.
Course Offerings in the Winter Semester 2026/27
For information about the upcoming introductory class “Einführung in die Praktische Informatik (IPI)” as well as the seminar “Agentic AI for Problem Solving” and software practicals offered by our group, see our winter semester 2026/27 courses.
Highlights
Our Research
Our research focuses on AI-driven methods that are common in many application domains, including intelligent search, knowledge graphs, neurosymbolic computing, reasoning, and conversational AI.
Our Teaching
We teach the enduring principles of data science and work to keep every course current with the latest methods and tools — from databases and text analytics to large language models and complex network analysis.
Our Team
Meet the people behind our work — a dedicated, interdisciplinary team driven by curiosity and a shared passion for both fundamental and application-oriented research.