Patrick Erdelt
Professor Für Mathematik Und Datenbanksysteme
Berlin, Germany
Summary
👤
Senior🎓
Top SchoolPatrick Erdelt is a Berlin-based professor of Mathematics and Database Systems with over a decade of experience bridging applied research, teaching, and industry practice. He leads the Numerical Mathematics lab and plays a central role in Data Science program governance and examination at the Berliner Hochschule für Technik, after a long professorial tenure at Beuth University. His background spans doctoral-level mathematics and theoretical physics, hands-on IT project leadership for SMEs, and founding a web engineering agency—combining theoretical rigor with practical system design and data quality governance. Known for translating abstract mathematical insight into teachable tools and reliable database solutions, he also brings experience in curriculum development and staff training that strengthens institutional data science capabilities.
10 years of coding experience
2 years of employment as a software developer
Dr. phil. nat., Mathematics, Dr. phil. nat., Mathematics at Goethe-Universität Frankfurt am Main
Github Skills (26)
benchmark10
python10
python-interface10
ycsb10
hpc-cluster10
benchmarking10
aws10
sql10
yahoo10
database-management10
configurations10
blackbox10
database10
dashboard9
dbt9
Programming languages (4)
Github contributions (5)
Beuth-Erdelt/DBMS-Benchmarker
Oct 2019 - Feb 2023
DBMS-Benchmarker is a Python-based application-level blackbox benchmark tool for Database Management Systems (DBMS). It connects to a given list of DBMS (via JDBC) and runs a given list of parametrized and randomized (SQL) benchmark queries. Evaluations are available via a Python interface and on an interactive multi-dimensional dashboard.
Contributions:49 releases, 4 reviews, 406 commits in 3 years 4 months
multi-dimensionalbenchmarkingdbmspythonparametrized
Beuth-Erdelt/Benchmark-Experiment-Host-Manager
Sep 2019 - Jan 2023
This python tool helps managing DBMS benchmarking experiments in a Kubernetes-based HPC cluster environment. It enables users to configure hardware / software setups for easily repeating tests over varying configurations.
Contributions:44 releases, 346 commits, 311 PRs in 3 years 4 months
dbmspythonbenchmarkingsetupsrepeating
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