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Field
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healthcare application needs to analyze sensitive patient data across distributed nodes. Researchers and students can explore privacy-preserving algorithms and technologies like federated learning and zero
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Anomaly detection is an important task in data mining. Traditionally most of the anomaly detection algorithms have been designed for ‘static’ datasets, in which all the observations are available
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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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algorithm development working with medical images, in particular CT or cone-beam CT a demonstrated ability to conduct research/scholarly activities outstanding interpersonal and communication skills in a team
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techniques to design new and efficient algorithms that can provide strong protection during the entire life cycle of ML models used on the devices. Research Task I: Investigate ML algorithms and optimisations
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and translation. CAD Frontiers is partnering with the Digital Sciences Initiative (DSI) at the University of Sydney to explore the convergence of digital sciences in information, algorithms and machine
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, conservation, evolutionary biology, marine science, neuroscience and science communication. The School supports approximately 600 coursework students and supervises over 100 PhD candidates. This role is based
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learning, algorithms, and programming. Prior exposure to reinforcement learning or human-robot interaction is highly desirable, though motivated candidates with a strong grounding in AI/ML and willingness
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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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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