Speaker
Description
Jan Kieseler is junior research group leader at the Karlsruhe Institute of Technology, and a member of the CMS experiment at CERN, convening one of the six physics analysis groups within the experiment, the top quark group, and the ML4RECO (machine learning for reconstruction) effort, where he developed dedicated AI architectures and techniques for one-shot (end-to-end) detection of physics objects directly from raw detector signals. He also used to coordinate the studies of the physics potential for the upgrades of the CMS detector targeting the end of this decade. Bringing together his AI background and the detector upgrades, he is one of the founding members of the MODE collaboration (machine learning optimised design of experiments), and in this context, he is investigating how modern AI tools can help us design the next generation of experiments.
