Computer science shapes the scientific profile of TU Darmstadt. Scientists research the technological foundations necessary for digitisation. In national and international comparisons, the TU always holds top positions. One key to the success of computer science at TU Darmstadt is the excellent networking with application disciplines in engineering and the humanities, especially in the research field Information and Intelligence “I+I”.
Oskar von Stryk belongs to an illustrious circle. He is the top-ranked researcher from Germany on a list dominated by researchers from US universities. It includes scientists from top universities such as Harvard, Stanford, Carnegie Mellon, Yale, MIT and Berkeley.
Von Stryk heads the Simulation, Systems Optimization and Robotics Group at the TU's Department of Computer Science. He researches the development of rescue robots that can autonomously search for people in the event of disasters or accidents. The rescue robots developed by his team have won numerous awards. Since 2018, von Stryk has been working to build the German Rescue Robotics Centre. He is a member of the AI•DA (Artificial Intelligence at TU Darmstadt) research initiative and the Hessian Centre for Artificial Intelligence (hessian.ai).
Kristian Kersting is head of the Artificial Intelligence and Machine Learning Group at TU Darmstadt. He is a member of the Centre for Cognitive Science, the AI•DA research initiative and the ELLIS Unit Darmstadt, as well as the founding co-director of the Hessian Centre for Artificial Intelligence. Kersting is a fellow of various professional societies. In 2019, he recieved the German AI Award.
About Academic Influence
Academicinfluence.com says its mission is to provide objective, non-gameable rankings for people, institutions and disciplines in higher education. To do this, the platform draws on innovative technologies that use machine learning to measure the global influence of top international academics. Among other things, the artificial intelligence uses data sources such as Crossref and Wikipedia, examines links and semantic information and weights these findings against sources such as periodicals, scientific journals and global media.