Johannes Ebke
Professor at Munich University of Applied Sciences
Munich, Bavaria, Germany
Summary
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Rockstar🎓
Top SchoolJohannes Ebke is a Professor and technology consultant with 17 years of experience bridging academic research and pragmatic software engineering, based in Munich. He holds advanced degrees in physics and mathematics (including a Dr. rer. nat. from LMU and an MASt from Cambridge) and transitioned from a senior consulting role at TNG to academia in 2020, where he combines teaching with applied development. His hands-on open-source work includes back-end contributions to the Ganga job-management frontend, improving Python job handlers and dataset handling for high-energy physics workflows. Johannes is equally comfortable refactoring task frameworks and shipping quality-of-life features like dry-run modes, reflecting a pragmatic focus on reliability and reproducibility. Colleagues describe him as a methodical problem-solver who translates complex scientific requirements into maintainable software and curricula.
17 years of coding experience
Ludwig Maximilian University of MunichVordiplom, Physics and Mathematics, Vordiplom, Physics and Mathematics at University of KonstanzMaster of Advanced Study, Mathematics, Master of Advanced Study, Mathematics at University of Cambridge
Github Skills (4)
python10
distributed-computing10
cer6
user-interface5
Programming languages (9)
Github contributions (5)
ganga-devs/ganga
Jan 2009 - Aug 2011
Ganga is an easy-to-use frontend for job definition and management
Role in this project:
Back-end Developer
Back-end DeveloperContributions:234 commits in 2 years 8 months
Contributions summary:Johannes primarily contributed to bug fixes and enhancements within the Ganga project, specifically targeting the AthenaMC application. Their work involved modifying Python code related to the AthenaMC job handler and related datasets, particularly fixing issues with event processing, partition handling and, dataset naming. The contributions also include refactoring code within the Task framework, as well as integrating additional features like a dry-run mode and other quality-of-life improvements such as the use of get-dataset.
golanguser-interfacecernlhcbdistributed-computing
JohannesEbke/cloudcomputing
Mar 2021 - Jul 2022
Vorlesung Cloud Computing
Contributions:1 review, 30 commits, 2 PRs in 1 year 4 months
vorlesungcloud-computingcloudkubernetescomputing
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