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and estimation Multi-agent planning and cooperation Communication-aware coordination strategies Learning-based control in networked systems Resilience and safety in multi-agent systems
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the theory of optimization algorithms and high-dimensional statistics to address some of the most fundamental questions in ML such as the behavior of neural networks. The environment of this project is highly
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systems, complex networks, data-driven modeling, machine learning, optimization, and sensor fusion. The division has extensive collaborations both with industry and other research groups around the
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the division of Geoscience and Remote Sensing we conduct research to tackle global environmental problems and to understand processes of the Earth system. We develop sensors, gather and analyse data
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monitoring. These applications rely on remote sensors to capture PCs and wirelessly transmit them to edge servers for downstream tasks, such as registration, i.e., aligning multiple PCs within the same 3D
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. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming
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successfully conducting research as well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks, data-driven modeling, learning control, optimization, and sensor
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to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. Read more: https://wasp-sweden.org/ . The vision of WASP is excellent research and competence in artificial