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Field
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-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation methods for data assimilation; and graph-based multi
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our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors
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for preventing and mitigating antagonistic threats in developing an integrated solution for digital twins from different domains (such as production, power grids, public infrastructure and spaces, logistics chains
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a set of use cases with energy community projects ranging from smart grid experimentation and energy sharing in rural regions in the Netherlands to developing an energy community in Amsterdam
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Vulnerability Detection of Smart Grids with a Specific Focus on Generative Adversarial Networks (GAN) Attacks Primary supervisors: Professor Damminda Alahakoon & Dr Shalinka Jayatilleke Other supervisors