Kasper Lauritzen
Machine Learning Engineer at Vestas
Copenhagen, Capital Region of Denmark
Summary
👤
Senior🎓
Top SchoolKasper Lauritzen is a machine learning engineer in Copenhagen with 13 years of experience building and deploying predictive models across energy, shipping, and finance. He combines academic rigor from an MSc/PhD background in nanoscience and theoretical physics with hands-on production skills—packaging models as APIs and frontends to give stakeholders actionable access. At DFDS he moved from model development to senior data scientist responsibilities, and he now applies probabilistic thinking to large-scale problems at Vestas. His open-source work includes core mathematical implementations for molecular RMSD calculations, reflecting a taste for numerical methods and clean algorithmic solutions. Colleagues describe him as driven by curiosity: his best satisfaction comes from understanding something new each day and turning that insight into reliable predictions.
13 years of coding experience
6 years of employment as a software developer
Master of Science (MSc), NanoScience, 12 (A+), Master of Science (MSc), NanoScience, 12 (A+) at Københavns UniversitetTheoretical and Mathematical Physics, Theoretical and Mathematical Physics at University of California, Santa Barbara
English, Danish, German
Stackoverflow
1,789reputation
115kreached
38answers
1question
machine-learning
top-5%
scikit-learn
top-5%
python
top-5%
Github Skills (20)
algorithm10
algorithms10
python10
data-structure10
numpy10
data-structures10
molecule9
machine-learning9
scikit-learn9
pdb9
testing7
code-coverage6
macos6
pycharm6
argparse6
Programming languages (14)
Github contributions (5)
charnley/rmsd
Oct 2015 - Jun 2017
Calculate Root-mean-square deviation (RMSD) of two molecules, using rotation, in xyz or pdb format
Role in this project:
Back-end Developer / Scientist
Back-end Developer / ScientistContributions:8 commits, 6 PRs, 4 comments in 1 year 8 months
Contributions summary:Kasper primarily focused on the core functionality of the `rmsd` library, contributing code to calculate the root-mean-square deviation of molecules. They made changes to rename files, correct imports, and implement various RMSD calculation algorithms including Kabsch and Quaternion methods. Additionally, the user added an example for usage and modified the test script for better error handling. The user worked on the core mathematical implementation used in calculating the RMSD.
rotationpdbatomsmoleculermsd
moneyball-dk/moneyball_app
Aug 2018 - Oct 2020
A webapp to track results of foosball games in financial institutions. It is a very niche market!
Contributions:6 releases, 243 commits, 92 PRs in 2 years 2 months
financialnichereactgamesfinancial-institutions
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