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Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
About me
CV
Curriculum vitae of Mario Andrés Muñoz Acosta: education, employment history, funding, teaching, and supervision.
Projects
Research projects, funded grants, and software platforms led by Mario Andrés Muñoz Acosta.
Publications
Journal articles, conference papers, and book chapters by Mario Andrés Muñoz Acosta on algorithm selection, instance space analysis, and black-box optimisation.
Teaching
Subjects taught by Mario Andrés Muñoz Acosta at The University of Melbourne and Monash University.
Posts
portfolio
ARC-Funded Research Projects
Published:
Competitive grant-funded research in algorithm analysis, benchmarking, and optimisation.
Industry Collaborations
Published:
Applied research with industry partners including AGL, Boeing Australia, and Future Fibre Technologies.
MATILDA – Melbourne Algorithm Test Instance Library with Data Analytics
Published:
Cloud-based platform for Instance Space Analysis, supporting rigorous algorithm benchmarking across multiple domains.
talks
Experiences publishing in Q1 Journals
Published:
Instance Space Analysis for Rigorous and Insightful Algorithm Testing
Published:
Tutorial on Instance Space Analysis methodology, co-presented with Kate Smith-Miles.
Instance Space Analysis for Rigorous and Insightful Algorithm Testing
Published:
Tutorial on Instance Space Analysis methodology, co-presented with Kate Smith-Miles.
Instance Space Analysis and Item Response Theory for Algorithm Testing
Published:
Tutorial combining Instance Space Analysis and Item Response Theory for algorithm testing, co-presented with Kate Smith-Miles and Sevvandi Kandanaarachchi.
Instance Space Analysis for Rigorous and Insightful Algorithm Testing
Published:
Tutorial on Instance Space Analysis methodology, co-presented with Kate Smith-Miles.
Instance Space Analysis for Rigorous and Insightful Algorithm Testing
Published:
Tutorial on Instance Space Analysis methodology, co-presented with Kate Smith-Miles.
teaching
Algorithms and Complexity
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.
Computational Modelling and Simulation
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.