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- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); Delft
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- Delft University of Technology (TU Delft); 17 Oct ’25 published
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completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation
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Challenge: Building self-organizing edge infrastructure that seamlessly adapts across terrestrial, cloud, and satellite networks. Change: Creating autonomous systems that unify edge orchestration
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mechanical stress into useful electrical energy, enabling autonomous sensors and systems in demanding industrial and structural environments. The research will involve a combination of analytical modelling
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are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we
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. This simple unit is limiting the learning capabilities of recurrent neural network models in tasks characterized by multi-timescale and long-range temporal dependencies. To implement multi-scale adaptation, in
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photovoltaics (PV) was identified by the IPCC as the technology with the highest potential among emission mitigation options. Scientific studies modelling energies scenarios for net zero emissions by 2050 project
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Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing power, latency, and memory bandwidth issues with reliable
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on sufficient and sufficiently clean water. However, we often lack the data to fully understand the dynamics of contaminants throughout the urban water cycle. Existing sensors for water quality monitoring do not
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description Cities depend on sufficient and sufficiently clean water. However, we often lack the data to fully understand the dynamics of contaminants throughout the urban water cycle. Existing sensors
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imaging systems capable of penetrating fog, dust, and even certain solid materials. These systems will deliver detailed, high-resolution imaging in challenging conditions where conventional optical sensors