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learning/artificial intelligence (ML/AI) techniques that incorporate uncertainty into visualizations, enhancing the efficiency and reliability of scientific discovery. It also offers exciting prospects
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to achieve equitable, reliable and adaptable built environments through data ecosystems creation, data science and integrated complex systems analysis. The group’s vision is to enable a sustainable, safe, and
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grid, concentrating on fortifying grid security, enhancing reliability, bolstering resilience and advancing decarbonization. Our primary focus lies in the comprehensive 'Everything-to-Grid' (X2G
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to investigate failure modes and ensure the reliability and longevity of RFB systems. Present and report research results and publish scientific results in peer-reviewed journals in a timely manner Ensure