Christoph Hasse

• Optimize Kalman Filter based particle trajectory and state estimation procedures. • Responsible for the LHCb experiment’s automatic performance profiling tests, which are an important part of the daily software validation procedure.

CERN Doctoral Student, funded by the Wolfgang Gentner Scholarship. My Ph.D. focused on optimizing LHCb's data processing pipeline to achieve the necessary throughput for LHCb's upgrade in 2021. This work consisted of improving the existing C++ algorithms as well as developing novel alternatives. - Software development in C++ & Python - Trained Neural Networks (e.g. LSTMs) in PyTorch - Profiling guided C++ optimization based on tools like Intel's VTune and Linux's perf.

• Extended the functionality of a framework for performing maximum likelihood fits on GPUs to enable a new form of physics analysis • Supervised one graduate student and two undergraduate students.

Development and support of Microsoft Excel macros in VBA