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Field
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to how latency, interference, reliability, incomplete observations, and limited wireless resources affect sensing, inference, and decision-making, and how communication and sensing resources can be
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beam (FIB) imaging - can be combined with AI to reconstruct nanoscale chip structures and infer functional behaviour from physical layouts. The project addresses the challenge of extracting reliable
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mechanistic and reliable service-life prediction models for concrete infrastructure, supporting improved durability design, maintenance planning and resilience of reinforced concrete structures exposed
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to the development of a multi-component framework for reliable and computationally efficient fatigue diagnosis and prognosis of steel structures. Building on the group's established expertise in virtual sensing and
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sits at the intersection of AI Safety and Data-Centric AI. We aim to make large-scale ML more reliable, transparent, and aligned with human values. We are specifically interested in: Data-centric AI
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renewable energy use, energy security, and the reliable operation of hydro-dominated power systems. The project will focus on how AI can support advanced optimization models for hydropower and energy-system
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) are increasingly used in civilian and defense applications such as surveillance, environmental monitoring, infrastructure inspection, etc. However, the platforms are mostly produced with passive structural
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sits at the intersection of AI Safety and Data-Centric AI. We aim to make large-scale ML more reliable, transparent, and aligned with human values. We are specifically interested in: Data-centric AI
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structures with extraordinary precision and do so quickly enough to keep up with large-scale production. This creates a fascinating computational challenge: how can we infer hidden physical properties from
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accessibility, and dependency on corporate-controlled resources. The project aims to develop data-efficient and reliable training strategies for vision foundation models, reducing the need for large datasets and