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humans and society at large is either fully automated or heavily relies on automatically provided decision support. While machine learning approaches become increasingly prevalent in this context
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work together, cooperative autonomous systems emerge. These systems hold transformative potential in applications like robotics, environmental monitoring, smart transportation, warehouse automation, and
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, Internet of Things, Systems-of-Systems automation, Machine Learning, Deep Learning, Data Science, Electronic systems design, and sensor systems. Cyber-Physical Systems (CPS) focuses on integrated software
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, Internet of Things, Systems-of-Systems automation, Machine Learning, Deep Learning, Data Science, Electronic systems design, and sensor systems. Cyber-Physical Systems (CPS) focuses on integrated software
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, Internet of Things, Systems-of-Systems automation, Machine Learning, Deep Learning, Data Science, Electronic systems design, and sensor systems. Cyber-Physical Systems (CPS) focuses on integrated software
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the interface between formal verification and automated planning. This is a unique opportunity to contribute to safer, more intelligent systems through a combination of theoretical work and practical
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, Internet of Things, Systems-of-Systems automation, Machine Learning, Deep Learning, Data Science, Electronic systems design, and sensor systems. Cyber-Physical Systems (CPS) focuses on integrated software
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developing AI methods for automated microstructure analysis and 3D microstructure generation. By combining self-supervised learning and diffusion-based generative models, the goal is to: Reconstruct high
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automated theorem provers and recently popularized for optimizing compilers and many other optimization tasks. We hypothesize that an e-graph would be an effective tool for discovering and encoding a large
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Join us for an exciting and excellent PhD journey to create the future of maintenance! Explore the fascinating future of Net Zero industries where complex and highly automated equipment need