Silvan Sievers - Software Engineer at Baloise CH

Silvan Sievers

Software Engineer at Baloise CH

Germany

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Summary

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Senior

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Top School

Silvan Sievers is an agile software engineer with 15 years of experience building open-source C++ and Python systems in the Linux ecosystem and a PhD-focused background in AI planning and search algorithms. He spent over a decade at the University of Basel as a PhD student and postdoctoral researcher, publishing and developing algorithmic heuristics and data-driven algorithm selection methods before moving into industry at Baloise CH. Beyond core research, Silvan contributes to notable open-source projects like the Fast Downward planning system, where he has implemented data-visualization tools used for experimental analysis. He combines a rigorous, analytical approach with a collaborative mindset, enjoying team discussions and clear explanations of complex ideas. Honest, curious, and goal-oriented, he gravitates toward challenging AI problems and practical engineering tasks that bridge symbolic and data-driven methods.

15 years of coding experience

6 years of employment as a software developer

Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Albert-Ludwigs-Universität Freiburg im Breisgau

Computer Science, Computer Science at ETH Zürich

Doctor of Philosophy - PhD, Computer, Doctor of Philosophy - PhD, Computer at University of Basel

English, German, French

Github Skills (5)

data-visualizations10

data-visualisation10

data-visualization10

python10

scientific-computing7

Programming languages (5)

C++ShellTeXPDDLPython

Github contributions (5)

aibasel/downward

Nov 2010 - Aug 2022

The Fast Downward domain-independent classical planning system

Role in this project:

Back-end Developer

Contributions:223 reviews, 2359 commits, 43 PRs in 11 years 10 months

Contributions summary:Silvan implemented a new version of a generalized scatter plot in experiments/issue851/generalscatter.py. This included writing a Python script using the Lab and Downward libraries, potentially for visualizing data in the context of a classical planning system. The code modifies plotting functions and classes, indicating a focus on data visualization and potentially performance analysis within the project. The primary tasks involved were code development.

classical-planningindependentdomainfast-downwardplanning

silvansievers/doko

Nov 2013 - Jun 2020

Contributions:23 commits, 4 pushes, 1 branch in 6 years 8 months

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