Challenges and Algorithms for Knowledge Discovery from Data

Arno Siebes graduated in Mathematics from Utrecht University in 1983. He joined CWI in Amsterdam in 1985, and obtained his Ph.D. in 1990 from Twente University. In 2000, he joined Utrecht University, where he took up the chair for Large Distributed Databases, which was later renamed to Algorithmic Data Analysis. He supervised 15 Ph.D. students, some of whom themselves became professors. His key research work has been on data mining and inductive databases. His most impactful contribution is using the minimum description length (MDL) principle for pattern mining, the algorithm known as Krimp led to an important subdomain in data mining. Arno has been a key member of the European data mining and machine learning community. In addition to his work on the Intelligent Data Analysis symposia, he was program co-chair of the first co-located edition of the European Conference on Machine Learning (ECML) and European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) and played a key role in the development of this thriving event.

Throughout his research and teaching career, Arno has maintained the philosophy that theory should work in practice. The contributions in this Festschrift serve as a reminder of his successes as a researcher and mentor. The chapters are categorized into topical sections on pattern mining, learning and reasoning, and large language models.