Pkrah webpage

content/authors/philipp-krah/_index.md

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+---
+authors: [ philipp-krah ]
+name: Philipp Krah
+email: philipp.krah@cea.fr
+title: Dr. Philipp Krah
+role: AI research engineer
+orcid: 0000-0001-8982-4230
+user_groups: [ "Permanent Staff" ]
+organizations:
+- name: CEA
+  url: https://www.cea.fr/
+- name: IRFM
+  url: https://irfm.cea.fr/
+social:
+- icon: envelope
+  icon_pack: fas
+  link: mailto:philipp.krah@cea.fr
+
+---
+
+Philipp Krah is a computational physicist with expertise in surrogate modeling, artificial intelligence (AI), and high-performance computing (HPC). He earned a Ph.D. in Applied Mathematics from TU Berlin, where he developed data-driven reduced-order models using AI and nonlinear reduction methods.
+His research focuses on incorporating physical information into data-driven approaches to improve their realibility and performance. He has published in leading mathematical and physical journals and has contributed to several open-source HPC projects, including WABBIT (Fortran, OpenMPI), CMM-turbulence (C++, CUDA), and GyselaX++ (C++, Kokkos). Currently, he is working on non-axisymmetric gyrokinetic plasma simulations for stellarators and integrating AI-based diagnostics and reduced-order models into GyselaX++ as part of the NumPEx Exa-DoST program.
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