Michael Berthold

Michael R. Berthold is a German computer scientist, entrepreneur, academic and author. He held the chair for bioinformatics and information mining at Konstanz University, and is an honorary professor at Óbuda University. He is also the co-founder of KNIME, and was serving as a president and CEO of KNIME AG from 2017 to 2025.

Berthold has authored over 250 publications while focusing his research on the use of machine learning methods for the interactive analysis of large information repositories. He is the editor and co-author of textbooks, including, Guide To Intelligent Data Science, and Intelligent Data Analysis.

Berthold is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), the past president of the North American Fuzzy Information Processing Society, and past president of the IEEE Systems, Man, and Cybernetics Society. He is an associate editor of Data Mining and Knowledge Discovery (DMKD), Knowledge and Information Systems (KIS), Journal of Cheminformatics (JCIS), and International Journal of Computational Intelligence in Bioinformatics and Systems Biology (IJCIBSB). He has been involved in the organization of various conferences, most notably the IDA series of symposia on Intelligent Data Analysis.

Early life and education Berthold was born in 1966 in Stuttgart, Germany. He received his MSc degree in computer science in 1992, and his Dr.rer.nat. degree in 1997, both from Karlsruhe University. From 2017 to 2025 he was full-time CEO at KNIME AG, Zurich, Switzerland.

At IEEE, Berthold served as a president of the IEEE System, Man, and Cybernetics Society from 2010 to 2011.

Research Berthold has focused his research on large and heterogeneous data sources, with a particular focus on methods from AI (rule learning, neural networks, fuzzy logic and general machine learning).

Fuzzy models Berthold has published on methods to extract fuzzy models from data based on constructive methods to build probabilistic neural networks. He developed similar algorithms for the extraction of fuzzy rule models. He then extended those models beyond classification and invented algorithms to extract regression models, so-called fuzzy graphs from data automatically.

Widening of machine learning algorithms Berthold was the first to introduce the idea of widened machine learning, which draws on parallel resources to improve model accuracy rather than the usual focus on speed-up. He discussed a number of generic ways of tuning data mining algorithms while providing a series of experiments. Later on, he conducted an in-depth analysis of the concept of Widened Data Mining, which aims at reducing the impact of heuristics by exploring more than just one suitable solution at each step. In 2017, Berthold and his team proposed the bucket selector, a model-independent randomized selection strategy, with the capability to perform better than existing selection strategies in cases without a diversity measure.

Data science design patterns In 2023, Berthold and his co-authors introduced the notion of visual design patterns for data science. The presented methods are using graph patterns, lending themselves naturally to the data flow paradigm underlying most data science tools.

Awards and honors 2001 – KS Fu Award, North American Fuzzy Information Processing Society 2010 – Fellow, The Institute of Electrical and Electronics Engineers (IEEE)