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Associated Research Groups Broaden the Scientific Spectrum
Research at the ML2R benefits from close cooperation with associated research groups from ML2R partner organizations. The cooperation in different basic or application-oriented research fields broadens the scientific spectrum of the ML2R. Here we introduce the heads of these research groups and their main areas of work.
Prof. Dr. Natalia Andrienko & Prof. Dr. Gennady Andrienko
Natalia Andrienko and Gennady Andrienko are lead scientists responsible for visual analytics research at Fraunhofer IAIS and full professors at City, University London where they both hold part-time teaching positions. They co-authored the monographs “Exploratory Analysis of Spatial and Temporal Data” (Springer, 2006), “Visual Analytics of Movement” (Springer, 2013) and “Visual Analytics for Data Scientists” (Springer, 2020) as well as more than 100 peer-reviewed journal papers. Several of their publications have been honored by prestigious awards such as test of time and best paper awards.
Gennady Andrienko was chairing the Commission on GeoVisualization of the ICA – International Cartographic Association from 2007 till 2015. Together with Natalia Andrienko, he co-organized scientific events on visual analytics, geovisualization and visual data mining, and co-edited 14 special issues of major journals. Gennady Andrienko is associate editor of the journals “Information Visualization” (since 2012) and “International Journal of Cartography” (since 2014) as well as editorial board member of “Cartography and Geographic Information Science” and “Cartographica”.
Natalia Andrienko is associate editor of “IEEE Transactions on Visualization and Computer Graphics” (since 2016) and “Visual Informatics” (since 2020) as well as editorial board member of “International Journal of Geographical Information Science”, “Journal of Geographical Systems” and “International Journal of Cartography”.
Prof. Dr. Sven Behnke
Prof. Dr. Sven Behnke has held the Chair of Autonomous Intelligent Systems at the University of Bonn since 2008 and is head of the Institute for Computer Science VI – Intelligent Systems and Robotics. In 1997, he graduated in Computer Science (Dipl.-Inform.) from the Martin Luther University Halle-Wittenberg and in 2002, he received his doctorate in Computer Science (Dr. rer. Nat.) from Freie Universität Berlin. In his dissertation “Hierarchical Neural Networks for Image Interpretation” he extended forward Deep Learning models to recurrent models for Visual Perception. In 2003, he did postdoctoral research on robust Speech Recognition at the International Computer Science Institute in Berkeley, CA. From 2004 to 2008, Sven Behnke led the Emmy Noether Junior Research Group “Humanoid Robots” at the Albert-Ludwigs-University of Freiburg. His research interests include Cognitive Robotics, Computer Vision and Machine Learning.
Sven Behnke received several Best Paper Awards, three Amazon Research Awards (2018-20), a Google Faculty Research Award (2019), and the Ralf-Dahrendorf-Prize of the BMBF for the European Research Area (2019). His team NimbRo has won numerous robot competitions (RoboCup Humanoid Soccer, RoboCup@Home, MBZIRC). In ML2R, Sven Behnke brings in his expertise in Deep Learning for Visual Perception to ML2R as an associated partner.
Prof. Dr. Jürgen Gall
Prof. Dr. Jürgen Gall has been Professor and Head of the Computer Vision Group at the University of Bonn since June 2013. He studied Mathematics at the University of Mannheim and the University of Wales Swansea, UK. After receiving his PhD in Computer Science from Saarland University and the Max Planck Institute for Computer Science, he was a postdoctoral researcher at the Computer Vision Laboratory of ETH Zurich from 2009 to 2012 and a Senior Research Scientist at the Max Planck Institute for Intelligent Systems in Tübingen from 2012 to 2013. He received a grant for an independent Emmy Noether research group from the German Research Foundation (DFG) in 2013, the German Pattern Recognition Award from the German Association for Pattern Recognition (DAGM) in 2014, and an ERC Starting Grant in 2016. Since 2017, he has been the spokesperson for the DFG-funded research group “Anticipating Human Behavior” at the University of Bonn. Gall’s research focuses on Action Recognition, Human Pose Estimation, and Object Detection and Segmentation.
Prof. Dr. Jens Lehmann
Jens Lehmann is Lead Scientist for Conversational AI & Knowledge Graphs at the Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS and coordinator of the Dresden site of Fraunhofer IAIS. In the department NetMedia, which focuses on Multimedia Pattern Recognition and Deep Learning, he further develops methods for data analysis for industry and research. Professor Lehmann’s main research areas at the institute are knowledge graphs, machine learning and question answering, dialogue systems. These topics he also deepens at his chair at the University of Bonn. He is one of the driving forces behind the Fraunhofer language assistance platform.
Professor Lehmann studied computer science at the TU Dresden and the University of Bristol (England). He received his doctorate at the University of Leipzig in 2010. Before being appointed to Bonn, Jens Lehmann led his own research group there since 2010. From 2013 until 2015 he was head of the Research Center for “Agile Knowledge Engineering and Semantic Web” (AKSW) at the University of Leipzig. From 2011 to 2012 he was a Research Visitor at the University of Oxford. His publications are frequently cited (h-index > 50) and have received several awards (more than 10 awards in international conferences and journals).
Prof. Dr. Dr. Wolfgang Rhode
Wolfgang Rhode studied physics at the University of Freiburg and completed a further study of philosophy with a doctorate. In 1993, he received his doctorate in physics from the University of Wuppertal. Wolfgang Rhode has both conducted research as well as taught at the Universities of Wuppertal, Berkeley and has held the professorship for astroparticle physics at TU Dortmund University since 2004. His research group is internationally renowned for their application of data analysis methods, which are implemented in various astrophysical experiments, including the large-scale projects IceCube, CTA, FACT, and MAGIC.
Together with the Chair of Artificial Intelligence, Wolfgang Rhode’s team conducts research within the Collaborative Research Center 876 “Providing Information by Resource-Constrained Data Analysis”, whose executive board he is a member of. Building on the long-standing collaboration of the scientific chairs, Wolfgang Rhode contributes his expertise as an associated partner within ML2R. In the Competence Center, he accompanies the relevant application field of astrophysics, which enables the research on and testing of ML methods in concrete use cases by means of large, non-personal data sets.