Jakob Thrane
Lead Machine Learning Engineer at TDC NET
Denmark
Summary
👤
Senior🎓
Top SchoolJakob Thrane is a Lead Machine Learning Engineer based in Denmark with nine years of experience bridging academic research and production AI systems, including a PhD focused on applying deep learning to next-generation mobile communications. He has led ML-driven digital twin and GIS workflows, built large-scale medical imaging pipelines for a 1.2M x-ray dataset, and architected enterprise-grade data orchestration using Dagster and MLflow. Comfortable across Python, PyTorch, Golang and systems profiling, Jakob combines hands-on optimization of CPU/GPU bottlenecks with pragmatic software engineering to move models from research to near-real-time production. Notably, his background spans both telecom R&D (including a visiting role at Nokia Bell Labs) and startup CTO/architect experience, giving him a rare mix of domain depth and delivery-focused leadership.
9 years of coding experience
8 years of employment as a software developer
Telecommunication, Telecommunication at Huawei Telecom Seeds For The FutureMaster's Degree, Telecommunications Engineering, Master's Degree, Telecommunications Engineering at Danmarks Tekniske UniversitetBachelor of Science (BS), Telecommunication engineering, Bachelor of Science (BS), Telecommunication engineering at Universidade Federal do Espírito SantoTechnical University of Denmark
English, German, Danish
Github Skills (26)
toolbox10
matlab10
monster10
loss10
lte9
prediction9
satellite8
satellite-images8
openstreetmap8
multimodal6
python6
convolutional-neural-networks6
deep-learning5
machine-learning5
pytorch4
Programming languages (4)
Github contributions (5)
Sonohi/monster
Feb 2017 - May 2020
MONSTeR is a framework built around the LTE system toolbox available in Matlab
Contributions:2 releases, 363 commits, 66 PRs in 3 years 3 months
toolboxltemonstermatlab
jakthra/PseudoRayTracingOSM
Feb 2020 - Aug 2020
Conv nets applied to OSM maps for path loss prediction
Contributions:22 commits, 18 pushes, 3 branches in 6 months
openstreetmapconvpredictionnetsloss
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