Speaker
Johannes Albrecht
(TU Dortmund & LAMARR)
Description
High-energy particle physics experiments are on the brink of facing significant challenges in reconstructing complex events due to increasing intensities and energies. The scientific aim of the presented work is to address the growing computational complexity of event reconstruction while enhancing efficiency and improving the precision of analyses in the ATLAS, LHCb, and Belle II experiments. To achieve this, the work has two primary objectives. First, it will advance machine learning (ML)-based algorithms for track and vertex reconstruction and event interpretation, integrating these methods into the reconstruction software of these experiments. Second, it will contribute to the development of cross-experiment platforms.
