Room: 03-617
Johannes Gutenberg – Universität Mainz
Institut für Informatik
Staudingerweg 9
55128 Mainz, Germany
For requests and questions regarding my role as AI Pilot of Rhineland-Palatinate (KI-Lotse des Landes Rheinland-Pfalz) for the life sciences, please contact:
E-Mail: ki-lotse-rlp@uni-mainz.de
Julia Reichenpfader
Phone: +49 6131 39-36094
E-Mail: kramer [at] informatik [dot] uni [dash] mainz [dot] de
Office Phone: +49 6131 39-26787 (Sylvia Steinmetz) or +49-6131-39-27851 (Kaija Krüger)
For requests concerning thesis topics, lectures or teaching related inquiries, please write to datamining@uni-mainz.de
Research Interests
- Machine learning and data mining on structured data: sequences, strings/text, trees, graphs, logics, time series, ...
- Knowledge and (machine) learning
- Stream mining
- Data mining and machine learning under constraints like privacy, confidentiality and transparency
- Computational scientific discovery
- "So good" applications: applications of data mining and machine learning for social good, in medicine/in the life sciences, in computational sustainability (energy, mobility, ...), ...
Current Activities
- AI Pilot of the State of Rhineland-Palatinate
- Spokesperson of the TOPML Project (Trading Off Non-Functional Properties of Machine Learning) funded by Carl Zeiss Foundation
- Steering Committee Member of the BMFTR Cluster for Future curATime
- General Chair and Program Chair of the 2nd International Conference on AI for Science (AI4Sci 2026) and the 29th International Conference on Discovery Science (DS 2026)
- BMFTR Plattform Lernende Systeme AG2: Technologische Wegbereiter und Data Science
Publications
Computer science publications (DBLP): https://dblp.org/pid/k/StefanKramer1.html
Life science publications (PubMed collection): https://www.ncbi.nlm.nih.gov/myncbi/browse/collection/57464698/?sort=date&direction=descending
Google scholar: https://scholar.google.de/citations?user=0QXx46sAAAAJ&hl=de&oi=ao
LinkedIn: https://www.linkedin.com/in/stefan-kramer-70854125/
Bio
1994-1999 Austrian Research Institute for Artificial Intelligence (group of Prof. Gerhard Widmer), 1994-1999 Siemens AG Austria Program and Systems Engineering (group of Prof. Hermann Kaindl), 1999 Dr. techn. from Technische Universität Wien, 2000-2002 University of Freiburg (chair of Prof. Luc De Raedt), 2003-2011 Associate Professor at the Computer Science Department of Technische Universität München, 2011- Full Professor at the Institute of Computer Science of Johannes Gutenberg University Mainz, 2012-2016 and 2020-2022 Vice General Manager of the Institute of Computer Science, 2016-2018 and 2022-2024 General Manager of the Institute of Computer Science, 2017- Honorary Professor of the University of Waikato, 2024- AI Pilot of the State of Rhineland-Palatinate as appointed by the Prime Minister
More than 200 peer-reviewed publications, thereof more than 180 peer-reviewed conference and journal publications; program committee member of more than 120 conferences or workshops; supervision of more than 100 BSc, MSc, diploma theses and more than 15 completed PhD theses; acquisition of more than 30 projects, funded by the European union, the DFG, BMBF, the Carl Zeiss foundation, industry, and others. Only active university professor in the German speaking countries with contributions to the first international conferences on data mining (KDD '95, KDD '96, KDD '97).
Awards
Best Application Paper Runner-Up: 7th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2001); Best Theory Paper: 16th International Conference on Inductive Logic Programming (ILP-2006); Best Application Paper: 8th IEEE International Conference on Data Mining (ICDM-2008); Senior Author of Best Student Paper: 8th IEEE International Conference on Big Knowledge (ICBK-2017); Best Paper: 10th IEEE International Conference on Big Data (ICBK-2019), Ig Nobel in Chemistry 2021
Professional Activities
General
2008-2016, 2018- Editorial Board of Machine Learning; Vice-Chair of the 13th IEEE International Conference on Data Mining (ICDM-2013); (Co-)Organizer of the first ECML/PKDD in 2001 in Freiburg; Workshop and Tutorial Chair of the 14th European Conference on Machine Learning (ECML-2003) and the 7th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD-2003); Highlights Track Area Chair of: ISMB 2012, ISMB/ECCB 2013, ISMB 2014, ISMB/ECCB 2015; Area Chair of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases: ECML/PKDD-2017, ECML/PKDD-2014, ECML/PKDD-2013, ECML/PKDD 2007, ECML/PKDD-2006; Data Mining Track Chair of the ACM Symposium on Applied Computing (SAC-2014, SAC-2015, SAC-2016, SAC-2017); senior PC member of IJCAI/ECAI-2018, IJCAI-2015, IJCAI-2013, IJCAI-2011; Organizer of the Predictive Toxicology Challenge 2000-2001
Spokesperson of the Network for Deep Continuous-Discrete Machine Learning (DeCoDeML) of the Rhein-Main universities (Johannes Gutenberg University Mainz, Technische Universität Darmstadt, Goethe University Frankfurt), member of the following boards: BMBF Plattform Industrie 4.0: AG2/Projektgruppe Künstliche Intelligenz, KI Board Rheinland-Pfalz, ZIRP Advisory Board, Projektgruppe Data Literacy Education (DLE) @ JGU, Projektgruppe der Koordinationsstelle Digitaler Wandel in Studium und Lehre (DWSL) @ JGU, Projektgruppe KI@JGU
Program (Co-)Chair of Events
Program Chair of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD) 2021, 15th International Conference on Inductive Logic Programming (ILP-2005); 5th International Workshop on Machine Learning in Systems Biology (MLSB-2011); OpenTox Euro 2013 Meeting; OpenTox Euro 2011; ECML/PKDD-2017 Workshop on Data Mining for Social Good (SoGood-2017); ECML/PKDD-2017 Workshop on Data Mining with Secure Computation; ICML-2007 Workshop on the Induction of Process Models (IPM-2007); ECML/PKDD-2008 Workshop on the Induction of Process Models (IPM-2008); ECML/PKDD-2001 Workshop on The Predictive Toxicology Challenge; ICML-2000 Workshop on Attribute-Value and Relational Learning: Crossing the Boundaries