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architectures, implement co-evolutionary algorithms, and develop rigorous evaluation frameworks measuring adversarial robustness. Outputs include an agent-based simulation toolkit, stress-testing methods, and
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privacy regulations and rare-event scarcity. Traditional case-based training relies on limited historical examples, leaving investigators poorly prepared for emerging threats. This PhD will develop and
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visual inspection. The research will address several challenges: Complex Surfaces: Developing robust algorithms (leveraging Convolutional Neural Networks and Transformers) capable of identifying tiny
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