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The world is dynamic, in constant flux. However, machine learning typically learns static models from historical data. As the world changes, these models decline in performance, sometimes
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. This program of work will engage three PhD students, each from a different background (technical, psychology, design/HCI), to contribute their expertise towards enhancing the helpline service and improving
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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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, infer arbitrarily closely to any model underlying data. We endeavour to do the following: Apply MML to test datasets (degenerate motifs of 6-12 base pairs and with 1 to 2 variable nucleotides) Apply MML
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Cybersecurity is an interdisciplinary field. There is an urgent need to build up talent in human factors in cybersecurity. This PhD will provide the candidate with a unique pathway into industry
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Current federated learning architectures in mobile healthcare are limited to a centralised model without considering the full continuum of mobile-edge-cloud. Additionally, to support different data
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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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analysis, contextual analysis, audio feature extraction, and machine learning models to identify and assess potentially dangerous content. Similarly, computer vision models are implemented to analyse images
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This project will result in a much fuller understanding of the state of the Birrarung than is currently possible, as well as qualitative and quantitative results to model different interventions and
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is highly complex. For the proposed PhD project, experimental data are already available that bring together maps of orientations of such crystals together with the deformation pattern generated during