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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data
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-based, probabilistic, and in-memory computing, are based on a wide variety of physical processes, materials, architectures, and algorithms. For effective implementation, these aspects need to be mapped
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challenges raised by the increased digitalisation of society. Our in-house iLab develops value-based prototypes and designs. Researchers at iHub are organised around themes, such as algorithmic discrimination
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space systems; Investigating and implementing PQC algorithms to safeguard space data systems against quantum computing threats; Evaluating the performance and security of PQC solutions in the context
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Future-Proof Smart Logistics. It aims to contribute to the realisation of the PI concept by developing advanced machine learning-based decentralised decision-making algorithms. These algorithms will enable
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of stroke patients and healthy volunteers. Developing algorithms for identifying and excluding motor unit filters associated to impaired motor units. Integrating real-time-decoded features of motor unit
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understand data, and then make useful predictions based on it. These algorithms integrate insights from various fields, including statistics, artificial intelligence and neuroscience. To find more information
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this project, we aim to: Develop real-time ultrasound algorithms to estimate fascicle length in antagonistic leg muscles (tibialis anterior and soleus) in healthy individuals during walking. Translate and
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) and cover a wide range of innovative topics, from the development and validation of novel methods, algorithms and EO products to innovative climate research; the development of improved climate data