MCML - Board of Directors
Bernd Bischl
Prof. Dr.
Director
Statistical Learning & Data Science
Bernd Bischl
holds the Chair of Statistical Learning and Data Science at the Department of Statistics at LMU Munich.
He studied Computer Science, Artificial Intelligence and Data Sciences in Hamburg, Edinburgh and Dortmund and obtained his PhD from Dortmund Technical University in 2013 with a thesis on "Model and Algorithm Selection in Statistical Learning and Optimization". His research interests include AutoML, Model Selection, Interpretable ML, as well as the development of Statistical Software. He is a member of ELLIS in general, and a faculty member of ELLIS Munich, an active developer of several R-packages, leads the "mlr" (Machine Learning in R) engineering group and is co-founder of the science platform "OpenML" for open and reproducible ML. Furthermore, he leads the Munich branch of the Fraunhofer ADA Lovelace Center for Analytics, Data & Applications, i.e. a new type of research infrastructure to support businesses in Bavaria, especially in the SME sector.
Daniel Cremers
holds the Chair for Computer Vision and Artificial Intelligence at TU Munich since 2009.
In 2002 he obtained a PhD in Computer Science from the University of Mannheim, Germany. Subsequently he spent two years as a postdoctoral researcher at the University of California, Los Angeles (UCLA) and one year as a permanent researcher at Siemens Corporate Research in Princeton, NJ. From 2005 until 2009 he was associate professor at the University of Bonn, Germany. In 2016, Prof. Cremers received the Gottfried Wilhelm Leibniz Award, the biggest award in German academia.
Daniel Rückert
is Alexander von Humboldt Professor for AI in Medicine and Healthcare at TU Munich. He is also a Professor at Imperial College London.
He gained a MSc from Technical University Berlin in 1993, a PhD from Imperial College in 1997, followed by a post-doc at King’s College London. In 1999 he joined Imperial College as a Lecturer, becoming Senior Lecturer in 2003 and full Professor in 2005. From 2016 to 2020 he served as Head of the Department of Computing at Imperial College. His field of research is the area of Artificial Intelligence and Machine Learning and their application to medicine and healthcare.
Thomas Seidl
is Professor for Computer Science and head of the Database Systems and Data Mining Chair at LMU Munich.
His fundamental research on data mining and database technologies with application domains in engineering, business, life science and humanities yielded more than 300 scientific publications so far. He serves on many program committees and scientific boards and is co-chair of the LMU Data Science Lab, the ZD.B Innovation Lab, the Munich School of Data Science @Helmholtz, TUM and LMU (MuDS) and of the Elite Master program in Data Science at LMU.
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