Fabio Gratl

Dr. Fabio Gratl is a former Researcher (Wissenschaftlicher Mitarbeiter) at the Chair of Scientific Computing in Computer Science (SCCS) at the Technical University of Munich (TUM). He holds a M.Sc. in Informatics from TUM (2017) and completed his doctoral studies (Dr. rer. nat.) in 2020. His research focuses on high-performance computing, molecular dynamics simulations, and auto-tuning algorithms for particle systems. He contributed to the development of the AutoPas library, which enables node-level auto-tuning for optimal performance in molecular dynamics.

Key research interests include parallel computing (shared memory/task-based/mpi), vectorization, and algorithm selection strategies. He has advised numerous theses on topics like GPU acceleration, auto-tuning with machine learning, and space debris modeling. His work integrates software development (C++, Python) with computational engineering challenges.

Teaching activities included courses on scientific computing, molecular dynamics, and numerical programming at TUM. He also organized seminars on leadership and future HPC trends. Notable software contributions include AutoPas, ls1 mardyn extensions, and tools for polyhedral gravity modeling.

Publications span computational science journals and conferences, emphasizing algorithm optimization and cross-domain applications. Despite leaving the SCCS chair, his research legacy persists through ongoing AutoPas development and collaborations.