Eigil Lippert
Academic Support Teacher at DTU - Technical University of Denmark
Copenhagen, Capital Region of Denmark
Summary
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Top SchoolEigil Lippert is a machine learning and modelling engineer and PhD researcher with eight years’ experience applying AI and physics-based methods to Earth observation and ice-sheet modelling. He builds robust model pipelines for large, complex satellite image formats and explores scientific machine learning (including PINNs) to accelerate glacier simulations and reduce inference time. His background spans hands-on fieldwork—from Arctic GNSS deployments to certified emergency-response operations—giving him a pragmatic, calm-under-pressure approach to problem solving. At DTU he supports students with learning needs, translating complex numerical and data-science concepts into structured, actionable workflows. International research stints at JPL, Dartmouth and EPFL underline his ability to bridge C++ simulation backends, deep learning, and remote-sensing data. He is motivated by work that couples analytical depth with tangible climate impact.
7 years of coding experience
4 years of employment as a software developer
Exchange stay, Machine Learning and statistics, Exchange stay, Machine Learning and statistics at EPFLTechnical University of Denmark
English, Danish, French, Italian
Github Skills (18)
sar9
insar9
earth-observation7
julia7
python6
machine-learning5
observation4
data-repository4
data-science4
earth4
common-data-format3
image-processing3
zarr3
data-format2
image-library2
Programming languages (4)
Github contributions (5)
eyhl/Modeling-a-century-of-change-Kangerlussuaq-Glacier-1933-to-2021
May 2022 - Jan 2023
Contributions:1 release, 3 commits, 58 pushes in 8 months
eyhl/premis
Apr 2022 - May 2022
Contributions:40 pushes, 4 branches in 29 days
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