Leon Overweel
Tech Lead - Power Forecasting at Dexter Energy
Amsterdam, North Holland, Netherlands
Summary
👤
Senior🎓
Top SchoolLeon Overweel is a tech lead specializing in ML-driven power forecasting for renewables, with a decade of experience building and scaling short-term wind, solar, prosumption and demand prediction systems for energy traders and grid operators. He combines research-grade ML competence (MSc AI) with hands-on engineering leadership, keeping customer-facing forecasters top-ranked in accuracy while shipping new product capabilities slated for 2025. Past work spans energy-efficient deep learning at Plumerai—contributing to open-source Larq and operational research tooling—and contributions to TensorFlow Datasets integration work. Based in Amsterdam, he also runs a biweekly newsletter on productized AI and climate AI, signaling a rare blend of technical depth, communication skill, and domain-focused product thinking.
10 years of coding experience
7 years of employment as a software developer
MSc Artificial Intelligence, MSc Artificial Intelligence at The University of EdinburghHigh School, High School at Rye High SchoolBachelor’s Degree Computer Science and Engineering, Bachelor’s Degree Computer Science and Engineering at Delft University of TechnologySemester Abroad Machine Learning and Artificial Intelligence Minor, Semester Abroad Machine Learning and Artificial Intelligence Minor at National University of Singapore
English, Dutch, German
Stackoverflow
1,517reputation
237kreached
8answers
31questions
Github Skills (20)
python10
datasets10
tensorflow10
data-set9
numpy9
data-model9
machine-learning9
user-data9
h5py8
iphone6
dockerfile6
docker6
google-app-engine6
ssl6
facebook-messenger6
Programming languages (15)
Github contributions (5)
tensorflow/datasets
Feb 2020 - Mar 2020
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
Role in this project:
ML Engineer
ML EngineerContributions:9 commits, 1 PR, 13 comments in 1 month
Contributions summary:Leon primarily contributed to the NYU Depth V2 dataset integration within the TensorFlow Datasets repository. Their work involved modifying existing code for the dataset, including fixing split configurations, correcting import statements, and formatting code style. Furthermore, the user moved and updated a fake data generation script, ensuring the dataset's functionality and integration within the TensorFlow ecosystem. The user also fixed linting issues to maintain code quality.
datanumpydeep-learningdatasetmachine-learning
leonoverweel/leonoverweel.com
Feb 2019 - Jan 2022
Contributions:155 commits, 101 pushes, 1 branch in 2 years 11 months
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