Till Stensitzki
Forscher (Postdoktorand) at Universität Potsdam
Berlin, Germany
Summary
🤩
Rockstar🎓
Top SchoolTill Stensitzki is a Berlin-based postdoctoral researcher with 14 years of experience at the intersection of physics and scientific software development. With a Diplom and a summa cum laude doctorate in Physics from Freie Universität Berlin, he blends rigorous academic analysis with practical coding skills to advance research projects. He contributes to prominent open-source projects such as lmfit (enhancing confidence-interval calculations and robustness for nonlinear least-squares fitting) and matplotlib (fixing DPI/extent issues and improving core plotting internals). His work shows a knack for turning thorny numerical and edge-case problems into well-tested, maintainable code that benefits both researchers and the broader Python scientific community. Currently active at Universität Potsdam and Freie Universität Berlin, he pairs deep domain expertise with a pragmatic approach to tooling and reproducibility. Colleagues value him for meticulous statistical thinking and a preference for improving foundations rather than flashy features.
14 years of coding experience
Diplom, Physik, 1,0, Diplom, Physik, 1,0 at Freie Universität Berlin
Github Skills (10)
data-visualizations10
statistics10
scipy10
data-visualization10
data-visualisation10
python10
statistic10
matplotlib10
numpy9
back-end-development9
Programming languages (8)
Github contributions (5)
lmfit/lmfit-py
Apr 2012 - Aug 2022
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize, and with many additional classes and methods for curve fitting.
Role in this project:
Data Scientist
Data ScientistContributions:62 commits, 20 PRs, 12 pushes in 10 years 5 months
Contributions summary:Till primarily contributes to the `lmfit/lmfit-py` repository by adding and modifying code related to confidence interval calculations and model comparison. Their work includes implementing the `calc_ci` and `conf_interval` functions, as well as `conf_interval_2d`, which are crucial for statistical analysis within curve fitting applications. They also refactored the code to handle ill-defined problems and improved the search algorithms. Additionally, they added examples and testing.
linear-least-squaresminimizationpythonoptimizationadditional
matplotlib/matplotlib
Oct 2012 - Apr 2020
matplotlib: plotting with Python
Role in this project:Back-end Developer
Back-end DeveloperContributions:20 commits, 12 PRs, 119 comments in 7 years 7 months
Contributions summary:Till primarily contributed to the `matplotlib` library, focusing on internal improvements and bug fixes. They addressed issues in the `offsetbox` module related to DPI calculations and extent retrieval. Additionally, the user added tick rcParams and implemented modifications to the `axes` and `backend_bases` files, demonstrating a focus on enhancing the library's functionality and addressing performance issues. This work suggests a focus on the core functionalities and internal workings of the plotting library.
pythondata-sciencegtkdata-visualizationplotting
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