Title: Will AI Replace Scientists? From Papers to Insights with Large Language Models and Knowledge Graphs
Speaker: Prof. Michael Färber
Date: 16.10.2025, 4:40 PM–6:10 PM
Language: English
Format: Hybrid (Fritz-Foerster-Bau, Room 244 or online)

Abstract

Science is producing knowledge at a pace no human can follow. The challenge is no longer access to data, but uncovering meaningful insights. Knowledge graphs help by structuring complex information, while large language models (LLMs) provide reasoning to connect the dots. Together, they enable systems that can analyze millions of research papers, extract evidence-based insights, and turn scattered knowledge into understanding. This talk will explore how the combination of knowledge graphs and LLMs is changing the way we work with scientific literature and what this means for the future role of AI – and of scientists themselves.

Bio

Prof. Dr.-Ing. Michael Färber has been a Full Professor (W3) at the AI Center ScaDS.AI Dresden/Leipzig and TU Dresden, Germany, since April 2024, where he leads the “Scalable Software Architectures for Data Analytics” group. Appointed at the age of 36, he previously served as Deputy Full Professor for Web Science at the Karlsruhe Institute of Technology (KIT). His research focuses on Artificial Intelligence, in particular large language models, knowledge graphs, and graph neural networks, with links to neurosymbolic and explainable AI. Among the central themes of his work is scholarly data mining – developing AI systems that analyze millions of research papers to make scientific knowledge more accessible and trustworthy. He has authored over 120 peer-reviewed publications at venues such as ACL, EMNLP, ISWC, CIKM, KDD, and NAACL, and has received multiple Best Paper Awards.