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My research focuses on the dramatic final stages of massive stars, exploring how they end their lives as gamma-ray bursts, supernovae, and kilonovae. To unravel these mysteries, I employ a combination of multi-wavelength observational data with sophisticated simulations. I am a member of various...
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I am an ARC Future (former DECRA) Fellow and lead the Structured Nanophotonics Group at Monash University. My research in nanophotonics explores the full potential and multi-dimensional nature of light, focusing on controlled light-matter interactions at the nanoscale. Driven by the fascinating...
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explore current techniques such as fine-tuning, model alignment, prompt engineering and Retrieval Augmented Generation (RAG) to improve reliability of generated recommendations for two cases of chronic
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Many machine learning (ML) approaches have been applied to biomedical data but without substantial applications due to the poor interpretability of models. Although ML approaches have shown promising results in building prediction models, they are typically data-centric, lack context, and work...
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We have several PhD opportunities available in areas such as Multimodal Large Language Models (MLLM) for human understanding, MLLM safety, and Generative AI. If you have published in top-tier conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, etc.), you will have a strong chance of receiving a full...
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Please note that this PhD topic is offered exclusively at our Monash Malaysia campus and is not available at the Clayton campus. Core PhD Question How can we design future medical AI systems that remain secure, privacy-preserving, explainable, and clinically reliable when exposed to adversarial...
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potential remedial approaches - will be explored in this research program and they include (as examples): variability in staining outcomes across different stains and different sites (even within a given
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Background and Motivation Modern deep learning models have achieved remarkable success in computer vision and natural language processing. However, they typically produce overconfident predictions
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This project focuses on brain network mechanisms underlying anaesthetic-induced loss of consciousness through the application of simultaneous EEG/MEG and neural inference and network analysis methods. In this work we study the effects putative NMDA antagonists xenon, a potent anaesthetic, and...
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Relevant bibliography: - Chades, I., Carwardine, J., Martin, T., Nicol, S., Sabbadin, R., & Buffet, O. (2012). MOMDPs: a solution for modelling adaptive management problems. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 26, No. 1, pp. 267-273). - Blau, T., Bonilla, E....