Prof. Dr. Stephan Günnemann
Technical University of Munich
Department of Informatics - I26
Boltzmannstr. 3
85748 Garching b. München
Germany
Room: 00.11.059
Phone: +49 (0)89 / 289-17282
E-Mail: guennemann@in.tum.de
Research Focus
- Machine Learning for Graphs/Networks, Graph Neural Networks
- Reliable Machine Learning, Robust and Adversarial Machine Learning, Uncertainty Estimation
- Machine Learning for Temporal and Dynamic Data
Current Positions
- Executive Director of the Munich Data Science Institute
www.mdsi.tum.de - Professor (W3, tenured) for Data Analytics and Machine Learning
Professional Experience
- Executive Director of the Munich Data Science Institute
since October 2020 - Professor
Technische Universität München, Munich, Germany
since October 2016 - Research Group Leader
Technische Universität München, Munich, Germany
July 2015 - September 2016- funded by the Emmy Noether Program of the German Research Foundation (DFG)
- Research Scientist
Siemens AG, Siemens Research & Technology Center, Munich, Germany
February 2015 - June 2015 - Senior Researcher
Carnegie Mellon University, Pittsburgh, USA
October 2014 - February 2015 - Post-Doctoral Researcher
Carnegie Mellon University, Pittsburgh, USA
October 2012 - September 2014 - Visiting Researcher
Simon Fraser University, Vancouver, Canada
May 2011 - June 2011 - Research Associate
Data Management and Data Exploration Group, RWTH Aachen University
July 2008 - September 2012
- Promotion [Ph.D.] at the RWTH Aachen University (June 2008 - March 2012)
- Dissertation (Ph.D. thesis) "Subspace Clustering for Complex Data"
- Graduated with distinction "summa cum laude"
- Studies in Computer Science at RWTH Aachen Universiy (October 2003 - May 2008)
- Diplomarbeit (Master thesis) "Approximations for efficient subspace clustering in high-dimensional databases"
- Graduated with distinction
Academic Honors and Awards
- Heinz Maier-Leibnitz Medal, the highest scientific award of TUM, 2022
- Google Faculty Research Award in Machine Learning, 2019/2020
- Best Research Paper Award at the ACM SIGKDD Conference on Knowledge Discovery and Data Mining for the paper ``Adversarial Attacks on Neural Networks for Graph Data'', 2018
- Microsoft Azure Research Award, 2017
- Rudolf Mößbauer Fellowship of the TUM Institute for Advanced Study, 2016
- Emmy Noether Research Grant of the German Research Foundation (DFG) to set up an independent research group, 2015
- Young Researcher at the Heidelberg Laureate Forum, Heidelberg, Germany, 2015
- Best Student Paper Runner-Up Award for the paper ``Com2: Fast Automatic Discovery of Temporal ('Comet') Communities`` at the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2014
- Dissertation Award of the German Computer Science Society, Section on Databases and Information Systems, 2013
- DAAD Scholarship for postdoctoral research at the Carnegie Mellon University for the period 10/2013 to 09/2014
- Borchers-Plakette for doctoral dissertation "Subspace Clustering for Complex Data", 2013
- Travel Award for the paper ``Finding Contexts of Social Influence in Online Social Networks`` at the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Workshop on Social Network Mining and Analysis, 2013
- DAAD Scholarship for postdoctoral research at the Carnegie Mellon University for the period 10/2012 to 09/2013
- Best Paper Award for the paper "DB-CSC: A density-based approach for subspace clustering in graphs with feature vectors" at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2011
- Friedrich-Wilhelm-Preis for diploma thesis on "Approximations for efficient subspace clustering in high-dimensional databases", 2009
- Springorum-Denkmünze for Diplom (Master of Science) in Computer Science with overall mark 'excellent', 2009
- Schöneborn-Preis for the year's best Vordiplom (Bachelor degree equivalent) in Computer Science at the RWTH Aachen University, 2006