Konrad Heidler

Konrad Heidler holds the position of Chair of Data Science in Earth Observation at the Department of Aerospace and Geodesy, Technical University of Munich. He is an Earth observation specialist and research leader with expertise in deep learning and computer vision applications for environmental monitoring.

His research interests focus on applying AI to critical environmental challenges, particularly in the areas of:

• Reasoning and multi-modal deep learning for Earth observation data
• Permafrost disturbances analysis
• Glacial movement tracking
• Climate science applications
• Remote sensing technologies

His recent work demonstrates the application of AI to analyze millions of satellite images of retreating glaciers in Svalbard, revealing alarming rates of glacier shrinkage accelerating in response to climate change. His research combines computer vision techniques with environmental science to address pressing climate challenges.

He maintains strong industry connections through previous roles at the German Aerospace Center and Munich Re, bridging theoretical research with practical applications in insurance analytics and climate risk assessment.

His technical expertise includes proficiency in Python, JAX, PyTorch, and TensorFlow, with specialization in developing novel machine learning techniques, particularly self- and semi-supervised learning methods for processing large-scale geospatial datasets.