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detectors (Partial) automation of detector characterization for more efficient analysis Algorithm development: Development of a correction method based on information field theory for atmospheric image
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multi-parameter ion-beam tuning procedures (collaboration with Univ. of Vienna and HZDR) and developments of machine learning (ML)-algorithms for optimization of beam parameters and control of relevant
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control, state estimation, and path planning algorithms for single and multi-agent robotic systems (UAVs). develop and train AI models for practical applications such as real-time object detection and
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applications. Our overarching aim is to obtain a holistic view of interconnected biological systems in health and disease. We develop clearing technologies for cellular-level imaging and deep learning algorithms
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terrestrial system models, for example using data analysis methods, such as data assimilation, physical- or process-based machine learning, or deep learning algorithms Analysis of the effects of human
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Master Thesis - Development of ligand conjugated lipid nanoparticles for targeted T cell delivery...
holistic view of interconnected biological systems in health and disease. We develop clearing technologies for cellular-level imaging and deep learning algorithms (AI) to analyze large imaging and molecular
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Algorithm-HW-Codesign for wireless signal processing investigate novel hybrid imaging and coded excitation approaches for medical ultrasound reliable and resilient communications for critical applications in
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. The research area includes interactions between large oceanic currents, eddies, fronts, and the coast, as well as analyzing their effects on the distribution of heat, nutrients, marine life and the sea floor