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of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning
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use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical systems controlling complex energy systems like electric grids and thermal systems for a
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. TASKS: Mathematical modeling and development of inverse methods (e.g. Bayesian inversion, optimization based methods, sparsity promoting methods based on L1-norm minimization and compressed sensing
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: atmosphere.ei.tum.de ) Optimization of an urban sensor network configuration for greenhouse gas and air pollutant measurements using mathematical and physical assessments Analysis of ground-based and satellite-based
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Autonomous Challenge or EDGAR . Thereby, we research current problem fields in the areas of perception, planning, control, safety and evaluation. Our goal is always to develop the optimal overall software
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, maintaining and integrating a zoo of graph data systems is a huge challenge and leaves a lot of room for optimizations. Our vision is to explore opportunities to unify core parts of the different types
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network adaptation is crucial for optimal perfusion. In self-organizing life forms, network morphology constantly adapts in response to environmental stimuli towards more homogeneous distribu-tion of flow
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technology, and process optimization using mathematic modeling - Evaluate modified growth factors under real conditions with medium recycling - Independent work on research projects - Close cooperation with
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defined process for cultivated meat with material cycling - Optimize the process, also applying mathematic modeling, to improve yield and sustainability - Independent work on research projects - Close
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
Control we focus on research and teaching of control and optimization of cooperative, networked, and distributed dynamical systems. We develop novel methods and tools for the analysis and control