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software frameworks, algorithms, robust testing and validation methods, and/or empirically validated solutions that contribute directly to social good, promoting trust, fairness, transparency, and
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operators for these notions. Over the past fifty years, such non-classical logics have proved vital in computer science and logic-based artificial intelligence: after all, any intelligent agent must be able
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operators for these notions. Over the past fifty years, such non-classical logics have proved vital in computer science and logic-based artificial intelligence: after all, any intelligent agent must be able
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the area of structural health monitoring of civil engineering structures on an Australian Research Council Early Career Industry Fellowship project titled, 'Transforming Smart Bridge Monitoring by Computer
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This project aims to develop robust algorithms capable of identifying and analyzing fingertips extracted from both static images and video footage. Machine learning techniques, particularly computer
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experiments for months before the value of output y is measured for some given input x. This creates an exciting challenge for AI researchers to develop smart algorithms that can find the optimal value of input
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and polyploid crop species and benchmark them against other methods such as graph-based methods. This project will combine algorithm development and computational programming with large population
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queries, and automating data transformations. By combining advancements in natural language understanding, algorithm synthesis, and debugging, the proposed framework will enable developers to efficiently
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research on designing mobile energy hubs, energy systems integration, resilience analysis, and developing digital twin models and AI-enabled algorithms. You will conduct lab and field tests, analyse data
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This PhD project is part of a larger project that aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain