Kevin Donkers
Postgraduate Researcher
United Kingdom
Summary
👤
Senior🎓
Top SchoolKevin Donkers is a PhD researcher and data science engineer specialising in uncertainty quantification for agroforestry models to inform UK land‑use decisions toward Net Zero. With eight years' experience across research and operational teams at the Met Office, DELVE and the University of Exeter, he builds reproducible, collaborative data infrastructure using Python, R, cloud platforms and open‑source tools. He has contributed backend and full‑stack improvements to widely used Earth‑science libraries such as SciTools/iris and Cartopy, improving scientific visualisation and projection examples for the community. Awarded a UKRI policy internship and time at the Alan Turing Institute, Kevin bridges academic research, policy engagement and software engineering. Outside work he balances technical curiosity with adventurous pursuits—cycling long distances and experimenting in the kitchen—bringing practical grit to complex environmental problems.
8 years of coding experience
3 years of employment as a software developer
Ludwig Maximilian University of MunichMaster of Science - MSci, Chemical Physics, First Class, Master of Science - MSci, Chemical Physics, First Class at The University of GlasgowDoctor of Philosophy - PhD, Environmental Intelligence CDT, Doctor of Philosophy - PhD, Environmental Intelligence CDT at University of Exeter
English, German
Stackoverflow
46reputation
3kreached
3answers
0questions
Github Skills (18)
data-visualizations10
iri10
projection10
python10
matplotlib10
cartopy10
data-visualisation10
maps10
data-visualization10
intersystems-iris10
data-analysis10
testing9
geometry9
pep9
vis-network6
Programming languages (9)
Github contributions (5)
SciTools/cartopy
Nov 2017 - Nov 2018
Cartopy - a cartographic python library with matplotlib support
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:2 reviews, 25 commits, 7 PRs in 1 year
Contributions summary:Kevin primarily focused on improving the `utm_all_zones.py` example within the cartopy library. They refactored the example to use `fig.add_subplot()` for creating subplots and addressed code style with PEP8 compliance. The user also added an example to display all 60 UTM zones side-by-side. Further improvements included modifying documentation and a supporting script, `make_projection.py`.
python-librarycartopypythongeographyspatial
SciTools/iris
May 2018 - Oct 2018
A powerful, format-agnostic, and community-driven Python package for analysing and visualising Earth science data
Role in this project:Back-end Developer
Back-end DeveloperContributions:6 commits, 2 PRs, 23 comments in 5 months
Contributions summary:Kevin primarily focused on improving the `iris.quickplot` module, a core component for visualizing scientific data within the Iris library. Their contributions involved adding functionality, specifically the `axes` keyword argument, to ensure plot labels, titles, and the plot itself used the same axes. This included refactoring code and adding tests to ensure correct behavior. Furthermore, the user made minor documentation and UI adjustments.
pythonvisualisationagnosticgribatmosphere
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