Steffen Schotthoefer
Distinguished Staff Fellow (Householder Fellowship Mathematics In Computation)
Oak Ridge, Tennessee, United States
Summary
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Rockstar🎓
Top SchoolSteffen Schotthoefer is a Distinguished Staff Fellow at Oak Ridge National Laboratory with eight years of experience at the intersection of applied mathematics, machine learning, and scientific software. His PhD-focused trajectory at KIT and hands-on roles in research software engineering reflect deep domain expertise in simulation, adjoint methods, and computational fluid dynamics. As a contributor to the widely used SU2 open-source CFD suite, he implemented nuanced time-averaging and windowing functionality that integrated into adjoint solvers and optimization workflows. Steffen blends rigorous academic training with practical engineering—bridging algorithm development, Python tooling, and high-performance codebases—to deliver production-ready research software. Colleagues find his work notable for making advanced signal-processing features usable inside large multiphysics pipelines, a detail that often unlocks more reliable optimization results.
8 years of coding experience
2 years of employment as a software developer
Norges teknisk-naturvitenskapelige universitetMaster of Science - MS, Master of Science - MS at Technical University KaiserslauternDr. rer. nat. (PhD), Dr. rer. nat. (PhD) at Karlsruher Institut für Technologie (KIT)
German, English
Github Skills (7)
computational-fluid-dynamics10
fluid-dynamics10
c-language10
cprogramming-language10
signal-processing10
optimization9
python9
Programming languages (6)
Github contributions (5)
su2code/SU2
Oct 2019 - Apr 2021
SU2: An Open-Source Suite for Multiphysics Simulation and Design
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 reviews, 100 commits, 7 PRs in 1 year 5 months
Contributions summary:Steffen implemented and refactored functionality related to windowing functions for time averaging in a computational fluid dynamics (CFD) software suite. They added and removed windowing features within signal processing toolboxes, and integrated these functions into the adjoint solver and output routines. Their work included modifications to configuration structures, output files and modifications to the direct differentiation and shape optimization python scripts to correctly handle the new time averaging capabilities.
physicsmultiphysics-simulationpythoncfdsnl-applications
KiT-RT/kitrt_code
Apr 2020 - Jan 2023
A high performance framework for radiation therapy simulation and numerical solutions for kinetic equations.
Contributions:583 commits, 62 PRs, 493 pushes in 2 years 10 months
equationskinetictherapyfinite-volumedeep-learning
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