ARC-Funded Research Projects
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Competitive grant-funded research in algorithm analysis, benchmarking, and optimisation.
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Competitive grant-funded research in algorithm analysis, benchmarking, and optimisation.
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Applied research with industry partners including AGL, Boeing Australia, and Future Fibre Technologies.
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Cloud-based platform for Instance Space Analysis, supporting rigorous algorithm benchmarking across multiple domains.
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Tutorial on Instance Space Analysis methodology, co-presented with Kate Smith-Miles.
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Tutorial on Instance Space Analysis methodology, co-presented with Kate Smith-Miles.
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Tutorial combining Instance Space Analysis and Item Response Theory for algorithm testing, co-presented with Kate Smith-Miles and Sevvandi Kandanaarachchi.
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Tutorial on Instance Space Analysis methodology, co-presented with Kate Smith-Miles.
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Tutorial on Instance Space Analysis methodology, co-presented with Kate Smith-Miles.
Postgraduate compulsory subject, School of Computing and Information Systems, The University of Melbourne, 2018
COMP90038 is a mandatory postgraduate subject covering algorithm design, analysis, and complexity theory. Topics include sorting and searching, graph algorithms, dynamic programming, greedy algorithms, and NP-completeness.
Postgraduate elective subject, School of Computing and Information Systems, The University of Melbourne, 2022
COMP90083 is a postgraduate elective subject covering topics including Agent-Based Modelling, System Dynamics, Network Analysis, Optimisation, and Simulation techniques. The subject applies these methods to real-world complex systems across multiple domains. It was initially developed by Prof. Nic Geard in 2020.