Matthias aims to simplify the usage of Machine Learning by researching methods and developing tools that allow the usage of Machine Learning by domain scientists and also make it more efficient for expert users. His focus is on Automated Machine Learning (AutoML), which encompasses methods for hyperparameter optimization, meta-learning, and model selection. In addition, he embraces thorough benchmarking and researches tools and methods to support these. As part of these efforts, he is  also a member of the OpenML project, where researchers can share machine learning artifacts – mostly datasets – for collaborative research.

Since October 2025, Matthias Feurer is an Assistant Professor (Juniorprofessor) for Automated Machine Learning and Optimization at TU Dortmund University and faculty member of the Lamarr Institute for Machine Learning and Artificial Intelligence. Before joining TU Dortmund University, he was a Thomas Bayes Fellow of the Munich Center for Machine Learning and an interim professor at LMU Munich at the chair of Statistical Learning and Data Science. Previously, he was a PostDoc at the machine learning lab at the Albert-Ludwigs-Universität Freiburg, from which he also obtained his PhD.

• I wrote a blog post celebrating Auto-sklearn's 10th birthday at automl.space.
• I gave an invited talk at the AutoML workshop describing our work on Auto-sklearn 2.0 which can be found on Slideslive.
• Together with Katharina I gave an introduction to Auto-sklearn at the EuroPython 2021 which can be found on Youtube.
• We placed 1st in the warmstarting-friendly leaderboard of the BBO NeurIPS challenge.
• We wrote a blog post about meta-learning the arguments to Auto-sklearn, check it out at automl.org.
• Read our blog post on winning the 2nd AutoML challenge.
• Read our winning blog post of the kdnuggets blog contest on AutoML.
• Check out this interview with Aaron, Frank and me about the winning the AutoML challenge.
• Our work on Auto-sklearn got covered in the Computer Vision News.