Vytautas Jančauskas
Senior Scientist at German Aerospace Center (DLR)
Munich, Bavaria, Germany
Summary
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Senior🎓
Top SchoolVytautas Jančauskas is a Senior Scientist based in Munich with 16 years of experience at the intersection of computer science, statistics, machine learning and optimization, grounded by a PhD in Operations Research from Vilnius University. He has evolved from teaching and academic research into high-performance computing roles, leading work packages at the Leibniz Supercomputing Centre and now driving research at the German Aerospace Center (DLR). His practical software craftsmanship spans C, Cython and Python, with notable open-source contributions to scientific and data ecosystems—optimizing supernova simulation code in the widely used TARDIS project and enhancing plotting in pandas. He blends rigorous algorithmic thinking with performance engineering and has a track record of turning research prototypes into production-grade, benchmarked implementations.
16 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy (PhD), Operations Research, Doctor of Philosophy (PhD), Operations Research at Vilnius University
English, Lithuanian, Russian
Github Skills (21)
algorithm10
data-visualizations10
algorithms10
benchmark10
numerical10
python10
data-science10
matplotlib10
pandas10
benchmarking10
data-visualisation10
c1110
plot10
c1710
numerical-methods10
Programming languages (4)
Github contributions (5)
tardis-sn/tardis
Mar 2014 - Apr 2020
TARDIS - Temperature And Radiative Diffusion In Supernovae
Role in this project:
Back-end Developer
Back-end DeveloperContributions:306 commits, 18 PRs, 11 pushes in 6 years 2 months
Contributions summary:Vytautas primarily focused on implementing and optimizing core functionalities within the TARDIS project, specifically targeting the computational aspects of supernova modeling. Their contributions included re-implementing and optimizing the binary search algorithm in C, implementing various distance calculations, and porting and improving existing functions such as the macro atom and move packet functions. Furthermore, the user developed and implemented benchmark tests for performance analysis using asv.
pythonscienceastrophysicssupernovasupernovae
pandas-dev/pandas
May 2012 - Oct 2012
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Role in this project:Data Scientist
Data ScientistContributions:111 commits in 4 months
Contributions summary:Vytautas primarily contributed to the visualization aspects of the pandas library, specifically focusing on enhancements to plotting functions. They implemented and documented new features like `andrews_curves`, `lag_plot`, `bootstrap_plot`, `parallel_coordinates`, and `radviz`. Furthermore, the user significantly improved the `scatter_matrix` function by addressing label handling, adding test cases, and expanding the documentation. Their work involved modifying and extending plotting functionalities within the pandas library.
pythondatalabeled-datamanipulationdataframes
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