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joint initiative of Monash University and the Australian Federal Police, and researches the ethical application of AI theories and techniques to problems of interest to law enforcement agencies. The work
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guarantees of FL. In this project, we aim at an ambitious goal - designing secure and privacy-enhancing algorithms and framework for FL and applying our designs into real-world applications. To achieve
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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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designing and implementing new algorithms to produce visual aids to assist people to reason with causal Bayesian networks, as well as the planning and conduct of exploratory usability studies to assess
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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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The energy transition to net zero is in full swing! We at Monash University's Faculty of Information Technology (FIT) are in the unique position that we support the transition across an immensely
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traditional and advanced optimization techniques, including analytical models, simulation-based approaches, and data-driven algorithms. The research also considers practical constraints such as cost, process
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Learning for Data Efficiency. Design and implement novel active learning algorithms tailored for deep generative models. The system will iteratively evaluate its own performance and identify the most
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through its research. Key to this mission is the AiLECS (Artificial Intelligence for Law Enforcement and Community Safety) research lab. The AiLECS lab is a joint initiative of Monash University and the
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formative assessment and personalised feedback while ensuring fairness, accountability, and transparency. The research will explore a combination of algorithmic design, human–AI interaction, and empirical