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developed and implemented such methods for a plethora of non-classical logics [2]. But how can we guarantee that the implementation is faithful to the theory? Indeed, how can we be sure that we have not made
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algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have
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the development of Explainable AI Systems that can provide explanations of AI agent decisions to human users. Past work on plan explanations primarily focused on explaining the correctness and validity of plans. In
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at prediction and pattern recognition tasks but still fails at very simple planning and decision-making problems. This project will develop predictive and prescriptive analytics algorithms that combine
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This PhD project aims to mitigate the data scarcity of new NLP and Multimodal applications by developing novel active learning algorithms. In this project, the student will leverage large foundation
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Seizure prediction algorithms will be developed using the one-of-a-kind ultra-long-term human intracranial EEG dataset obtained from the Neurovista Corporation clinical trial of their Seizure
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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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PETs: This aspect requires a significant math background as it involves exploiting various mathematical results to develop a concrete cryptographic algorithm. Although desired, background in advanced
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science conference [1]; one of our papers is recognised as Clarivate Web of Science HighCite (top 1% of papers for the field of research) [2]; three of our algorithms (TS-Chief, InceptionTime and Rocket
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This project will investigate and develop the ways in which AI algorithms and practices can be made transparent and explainable for use in law enforcement and judicial applications The Faculty