Prof. Philipp Neumann (Photo: DESY, Marta Mayer)
DESY has a new head of IT: Philipp Neumann, who has also been named lead scientist and appointed professor for high performance computing and data science at Universität Hamburg. Neumann brings extensive experience on data- and HPC-driven research as well as running and managing HPC infrastructures. He takes over from Volker Gülzow, who retired last year.
Most recently a professor at the Helmut Schmidt University / University of the Armed Forces Hamburg (HSU), Neumann built his wide skillset and knowledge on scientific computing, high performance computing, and data science in various settings and disciplines. At HSU, he established an HPC competence platform including supercomputing infrastructure and performance engineering projects to support research groups in leveraging HPC platforms. With a focus on computational methods, his research addresses problems from various disciplines: these include the development of massively parallel simulation methods and software for fluids, with applications in thermodynamics, and process engineering or data analysis methods in medical applications. He further contributed to the centre of excellence in simulation of weather and climate in Europe before moving to HSU.
Neumann wants to maintain the outstanding cutting-edge IT activities taking place at DESY with regard to hardware and software, while also integrating the rapid technological developments inherent to scientific computing. “As a leading research centre in the field of matter, we need to further roll out and significantly advance computational science in this field, including research and development of data analysis methods, simulation technology, and, of course, artificial intelligence and machine learning. Our computing and data management infrastructures need to be both reliable and innovative, which is a challenge.” Both reliability and innovation as well as their optimal weighting are key to successful IT operations, Neumann muses, especially with artificial intelligence and machine learning rapidly evolving. “This also comprises the provision of researchers with adequate skillsets to make use of the infrastructures,” he adds.
To this end, he is leading an effort to build up a research group on computational methods for matter research, with focal points on data-based procedures concerning artificial intelligence and machine learning, data reduction and compression, and data analysis and simulation using high performance computing.
