David Schneller

David Schneller is a PhD candidate in Informatics at the Technical University of Munich (TUM), affiliated with the TUM School of CIT and the Department of Computer Science. He specializes in parallel computing and high-performance systems, with a focus on algorithm optimization for hardware architectures like Intel Broadwell and Xeon Phi. He has contributed to research in vectorization techniques and multi-body potential simulations, as evidenced by his publications in Parallel Computing.

Education:

• PhD candidate in Informatics (since 2023)
• M.Sc. Informatics (TUM, 2019-2023)
• M.Sc. Mathematics (TUM, 2020-2022)
• B.Sc. Mathematics (TUM, 2018-2020)
• B.Sc. Informatics (TUM, 2015-2019)

Teaching & Advising: Co-advised Master's thesis on GPU kernel generation for wave propagation (with Ravil Dorozhinskii). Currently teaches courses such as Scientific Computing II and leads seminars on wave simulation and professional development at TUM.

Labs/Teams: Active in the SCCS (Scientific Computing and Collision Systems) group, involved in software developments related to discontinuous Galerkin methods and Julia-based tools for wave propagation.