Konrad Heidler is a Senior Data Scientist and Earth observation specialist with 11 years of experience applying deep learning and computer vision to climate and remote sensing problems. He has led research groups at the Technical University of Munich and contributed to projects at the German Aerospace Center and Munich Re, bridging rigorous academic research (Ph.D. summa cum laude) with practical industry impact in insurance analytics and environmental monitoring. His work focuses on multi-modal reasoning and self-/semi-supervised learning for large-scale geospatial datasets, with hands-on expertise in Python, JAX, PyTorch, and TensorFlow. Known for translating novel ML methods into operational tools—such as automated drought and permafrost disturbance detection—he combines mathematical rigor from a Mathematics in Data Science MSc with a pragmatic engineering mindset. Based in Munich, he now applies this blend of research leadership and product-oriented data science at Hula Earth.
11 years of coding experience
4 years of employment as a software developer
Doctor's Degree, Artificial Intelligence, Summa cum Laude (1.0), Doctor's Degree, Artificial Intelligence, Summa cum Laude (1.0) at Technical University of Munich
Master of Science - MS, Mathematics in Data Science, 1.1, Master of Science - MS, Mathematics in Data Science, 1.1 at Technische Universität München
Semester abroad, Mathematics and Computer Science, Semester abroad, Mathematics and Computer Science at University of Exeter
Contributions:21 commits, 2 PRs, 14 pushes in 6 months
dopplerphonesandroidmeasurementandroid-app
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