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Field
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and optimization methods for Earth observation satellite networks with sensing, computing, and communication capabilities. The goal is to characterize the trade-offs between sensing accuracy, computing
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promising technology for producing large and complex metal component. Although its potential has been widely demonstrated, significant challenges remain in optimizing the process to ensure the quality
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simulation-assisted performance feedback regarding initial design concepts. We will explore how AI systems can augment professionals’ creativity toward concurrent optimization of human health and energy
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system. Examples of that could be: Develop a trajectory generation system that can provide near optimal trajectories including speed and accelerations constraints at the extreme points of the parcels under
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is a DDLS PhD student in Data driven cell and molecular biology. Data driven cell and molecular biology covers research that fundamentally transforms our knowledge about how cells function by peering
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support optimization of patient care. Whether this is achievable depends on the reliability of an AI-model. Testing of AI is often done on small numbers, and AI-models are not equally useful in all
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. MINDnet aims at addressing the challenge through a holistic optimization - from individual computing devices to the overall architecture, including a focus on applications, and training methods - across
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crucial role in the modelling, design, and optimization of various systems in product and process engineering. Despite significant progress made over the decades, existing thermodynamic models and theories
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. The lack of knowledge is related to the models that should be used to auralize UAM in urban environments: new models are needed to predict noise exposure in urban cities. Traditional aircraft noise studies
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-hardware co-design of neural architectures, memory hierarchies, and communication systems Model compression and optimization (pruning, quantization, knowledge distillation) for edge deployment FPGA- and ASIC