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Daniel Lusk is a researcher and PhD candidate specializing in sensor-based geoinformatics. His academic pursuits focus on uncovering global patterns in biodiversity through the lens of citizen science and Earth observation. His expertise includes plant trait modeling and the application of machine learning techniques, particularly machine and deep learning. Lusk has significant experience in bias reduction in geospatial data science, seeking innovative approaches to enhance the accuracy and utility of spatial data. He holds a Master of Science in Remote Sensing from the University of Potsdam, where he deepened his knowledge of geoinformation and visualization.
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Focus on Advanced Quantum Mechanics and experimental/theoretical electives.