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Theoretical computer science/ Artificial Intelligence
Every day, 40,000 trains race across Germany on the railway network. And every day, nearly 600 passenger aircraft roll across the tarmac at Frankfurt Airport, heading for the runway or gangway. Today‘s computers make decisions that are of great importance for our lives, not only in the transport sector. Experts speak of cyber-physical systems (CPS) when mechanical components are connected to each other via networks and modern information technology. These cyber-physical systems facilitate the management and control of complex systems and infrastructures.
But how can programming be developed to ensure that the interaction between computer/communication systems and physical movement works faultlessly so that collisions can be ruled out and no-one gets hurt? The point of departure for André Platzer's basic research is to make computer assistance systems so safe that we can trust them with our lives.
The decisions a machine makes are based on the logical conclusions it has been taught. In mathematical terms, CPS are dynamic systems because the components’ respective states change abruptly or continuously. Dynamic systems are described by differential equations. For these systems, André Platzer has pioneered the development of differential dynamic logics which allow them to be analysed and checked to verify that their decision-making is correct. Using differential dynamic logic, Platzer developed the open-source tool KeYmaera X, which is widely used in the community. It can test the correctness of a system’s conclusions and provide proof. In collaborations with government and industry (e.g., with Bosch, Siemens and Toyota), André Platzer's applied basic research has decisively improved the safety of CPS used in rail and air traffic as well as medical robotics.
At KIT, André Platzer is invited to head the Institute for the Reliability of Autonomous Dynamical Systems and create synergies with other fields of reliable dynamic CPS applications.
Brief bio
André Platzer received his doctorate in computer science from the University of Oldenburg in 2008. Since then, he has worked at the renowned Computer Science Department at Carnegie Mellon University, Pittsburgh, United States, where he was appointed to a full professorship in 2020. In 2015, he was briefly a visiting professor at Cornell University, Ithaca, United States, and in 2019, he conducted research as a Humboldt Fellow and DFG Mercator Fellow at TUM Munich. As early as 2009/2010, the magazines Popular Science and IEEE Intelligent Systems referred to him as one of the ten best young scientists in the field of AI.
