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, fairness). Provenance and integrity of machine learning pipelines. Generative content authenticity. Cyber-physical machine learning systems. Scalability of properties from small to large models. In
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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-engineering-and-automation/nonlinear-systems-and-control ) at Aalto University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees
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+to+apply#Howtoapply-Eligibility) a Master’s degree in Artificial Intelligence, Machine Learning, Computer Science, Cognitive Science, Psychology or a related field excellent knowledge in AI and at least one
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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at Aalto University (https://into.aalto.fi/display/endoctoralsci/How+to+apply#Howtoapply-Eli… ) a Master’s degree in Artificial Intelligence, Machine Learning, Computer Science, Cognitive Science