Johannes Fürnkranz

Johannes Fürnkranz is an AI researcher whose work spans machine learning, data mining and interpretable rule learning. He earned degrees at TU Wien and the University of Chicago, researched at the Austrian Research Institute for Artificial Intelligence and visited Carnegie Mellon before joining TU Darmstadt in 2004. At Darmstadt, he coedited Preference Learning, coauthored Foundations of Rule Learning, led AI work on the PRORETA 4 vehicle-safety project and became editor-in-chief of Data Mining and Knowledge Discovery. His JKU research includes the Bilateral Artificial Intelligence cluster and automated rule extraction from symbolic regression trees. He has been Professor for Computational Data Analytics at JKU Linz since October 2019, heads the Computational Data Analytics Group and coauthored an August 2026 paper proposing Glori for globally valid explanations of individual examples.

Now at: Johannes Kepler University of Linz
Born: 1975

Years link to their sources.

Timeline

1991–1994

Three degrees in computing

He earns a Diplom-Ingenieur in Computer Science at TU Wien in 1991 and a Master of Science at the University of Chicago in 1992. In 1994, he earns a doctor technicae at TU Wien.
1992–2003

Research and habilitation

From 1992 to 2002, he works as a researcher at the Austrian Research Institute for Artificial Intelligence. He serves as a visiting scientist at Carnegie Mellon University's CALD in 1997–1998. In 2001, he completes an Artificial Intelligence habilitation at TU Wien and receives Venia Legendi; from 2002 to 2003, he holds an APART stipend from the Austrian Academy of Sciences.
2002

Round Robin Classification

In 2002, he publishes “Round Robin Classification” in the Journal of Machine Learning Research.
2004–2019

Knowledge Engineering at Darmstadt

From 2004 to 2019, he serves as Professor for Knowledge Engineering at TU Darmstadt. In 2010, he coedits Preference Learning with Eyke Hüllermeier; he coauthors Foundations of Rule Learning with Dragan Gamberger and Nada Lavrač in 2012.
2015

PRORETA 4 and journal editorship

In 2015, he leads the Knowledge Engineering Group's AI work on PRORETA 4, a vehicle-safety project that uses machine learning to help prevent accidents. He begins serving as editor-in-chief of Data Mining and Knowledge Discovery in 2015.
October 2024–September 2029

Bilateral AI project leadership

From October 2024 through September 2029, he serves as a project leader for JKU’s Cluster of Excellence “Bilateral Artificial Intelligence.”
October 2025–September 2026

Automated rule extraction

He leads the JKU project “Automated Rule Extraction and Interpretation from Symbolic Regression Trees” from October 2025 through September 2026.
Since October 2019

Professor at JKU Linz

He is Professor for Computational Data Analytics at JKU Linz, co-affiliated with the LIT AI Lab since July 2021, and heads the Computational Data Analytics Group. His research spans machine learning and data mining, including inductive rule learning, multi-label classification, preference learning and formal description languages for interpretable if-then rules. In August 2026, he coauthors “Globally Valid Rule-Based Explanations for Black-Box Models,” which introduces Glori for globally valid explanations of individual examples.