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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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, synthetic aperture radar, and optical spectroscopy, while bringing new capabilities in areas such as innovative sensor development, retrieval algorithms, novel applications, and other forward-looking areas
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in their computation. We want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several
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includes signal processing with emphasis on development and optimization of algorithms for processing single and multi-dimensional signals that are closely related to applications and applied research
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sensors, but the methods could also be applied to other sensor types. The thesis work in the project will include the development of new methods, theoretical analysis, algorithm design, planning and
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, coordination, and decision-making algorithms for multiple autonomous agents—such as robots (robotic manipulators, drones, or vehicles)—that work together to achieve common goals in dynamic, uncertain
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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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environment project, we will develop automated species and community recognition, particularly focusing on pathogenic soil fungi, with help of deep-learning algorithms fed with microscopic image and Raman