Overview
Background
Marcus Gallagher is an Associate Professor in the Artificial Intelligence Group in the School of Information Technology and Electrical Engineering. His research interests are in artificial intelligence, including optimisation and machine learning. He is particularly interested in understanding the relationship between algorithm performance and problem structure via benchmarking. My work includes cross-disciplinary collaborations and real-world applications of AI techniques.
Dr Gallagher received his BCompSc and GradDipSc from the University of New England, Australia in 1994 and 1995 respectively, and his PhD in 2000 from the University of Queensland, Australia. He also completed a GradCert (Higher Education) in 2010.
Availability
- Associate Professor Marcus Gallagher is:
- Available for supervision
- Media expert
Fields of research
Qualifications
- Bachelor of Computer Science, University of New England Australia
- Postgraduate Diploma, University of New England Australia
- Doctor of Philosophy, The University of Queensland
Works
Search Professor Marcus Gallagher’s works on UQ eSpace
2017
Journal Article
Use of freely available datasets and machine learning methods in predicting deforestation
Mayfield, Helen, Smith, Carl, Gallagher, Marcus and Hockings, Marc (2017). Use of freely available datasets and machine learning methods in predicting deforestation. Environmental Modelling and Software, 87, 17-28. doi: 10.1016/j.envsoft.2016.10.006
2017
Conference Publication
Exploratory analysis of clustering problems using a comparison of particle swarm optimization and differential evolution
Saleem, Sobia and Gallagher, Marcus (2017). Exploratory analysis of clustering problems using a comparison of particle swarm optimization and differential evolution. 3rd Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2017, Geelong, VIC, Australia, 31 January – 2 February 2017. Heidelberg, Germany: Springer . doi: 10.1007/978-3-319-51691-2_27
2016
Journal Article
The importance of implementation details and parameter settings in black-box optimization: a case study on Gaussian estimation-of-distribution algorithms and circles-in-a-square packing problems
Bosman, Peter A. N. and Gallagher, Marcus (2016). The importance of implementation details and parameter settings in black-box optimization: a case study on Gaussian estimation-of-distribution algorithms and circles-in-a-square packing problems. Soft Computing, 22 (4), 1-15. doi: 10.1007/s00500-016-2408-3
2016
Journal Article
Towards improved benchmarking of black-box optimization algorithms using clustering problems
Gallagher, Marcus (2016). Towards improved benchmarking of black-box optimization algorithms using clustering problems. Soft Computing, 20 (10), 1-15. doi: 10.1007/s00500-016-2094-1
2015
Journal Article
Analysing and characterising optimization problems using length scale
Morgan, Rachel and Gallagher, Marcus (2015). Analysing and characterising optimization problems using length scale. Soft Computing, 21 (7), 1735-1752. doi: 10.1007/s00500-015-1878-z
2015
Conference Publication
Detecting anomalies in controlled drug prescription data using probabilistic models
Hu, Xuelei, Gallagher, Marcus, Loveday, William, Connor, Jason P. and Wiles, Janet (2015). Detecting anomalies in controlled drug prescription data using probabilistic models. 1st Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2015, Newcastle, NSW Australia, 5 - 7 February 2015. Heidelberg, Germany: Springer Verlag. doi: 10.1007/978-3-319-14803-8_26
2014
Journal Article
Detecting contaminated birthdates using generalized additive models
Luo, Wei, Gallagher, Marcus, Loveday Bill, Ballantyne, Susan, Connor, Jason P. and Wiles, Janet (2014). Detecting contaminated birthdates using generalized additive models. BMC Bioinformatics, 15 (1) 185. doi: 10.1186/1471-2105-15-185
2014
Conference Publication
Clustering problems for more useful benchmarking of optimization algorithms
Gallagher, Marcus (2014). Clustering problems for more useful benchmarking of optimization algorithms. 10th International Conference SEAL 2014, Dunedin, New Zealand, 15-18 December 2014. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-13563-2_12
2014
Journal Article
Sampling techniques and distance metrics in high dimensional continuous landscape analysis: limitations and improvements
Morgan, Rachael and Gallagher, Marcus (2014). Sampling techniques and distance metrics in high dimensional continuous landscape analysis: limitations and improvements. IEEE Transactions On Evolutionary Computation, 18 (3) 6595542, 456-461. doi: 10.1109/TEVC.2013.2281521
2014
Conference Publication
Fitness landscape analysis of circles in a square packing problems
Morgan, Rachael and Gallagher, Marcus (2014). Fitness landscape analysis of circles in a square packing problems. 10th International Conference, SEAL 2014, Dunedin, New Zealand, 15 - 18 December 2014. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-13563-2_39
2014
Conference Publication
A modified screening estimation of distribution algorithm for large-scale continuous optimization
Mishra, Krishna Manjari and Gallagher, Marcus (2014). A modified screening estimation of distribution algorithm for large-scale continuous optimization. 10th International Conference SEAL 2014, Dunedin, New Zealand, 15-18 December 2014. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-13563-2_11
2013
Journal Article
Estimating the intensity of ward admission and its effect on emergency department access block
Luo, Wei, Cao, Jiguo, Gallagher, Marcus R. and Wiles, Janet H. (2013). Estimating the intensity of ward admission and its effect on emergency department access block. Statistics In Medicine, 32 (15), 2681-2694. doi: 10.1002/sim.5684
2013
Journal Article
Parameter-free search of time-series discord
Luo, Wei, Gallagher, Marcus and Wiles, Janet (2013). Parameter-free search of time-series discord. Journal of Computer Science and Technology, 28 (2), 300-310. doi: 10.1007/s11390-013-1330-8
2013
Journal Article
Under voltage load shedding in power systems with wind turbine-driven doubly fed induction generators
Arief, Ardiaty, Dong, ZhaoYang, Nappu, Muhammad Bachtiar and Gallagher, Marcus (2013). Under voltage load shedding in power systems with wind turbine-driven doubly fed induction generators. Electric Power Systems Research, 96, 91-100. doi: 10.1016/j.epsr.2012.10.013
2013
Conference Publication
The Turing test track of the 2012 Mario AI championship: entries and evaluation
Shaker, Noor, Togelius, Julian, Yannakakis, Georgios N., Poovanna, Likith, Ethiraj, Vinay S., Johansson, Stefan J., Reynolds, Robert G., Heether, Leonard K., Schumann, Tom and Gallagher, Marcus (2013). The Turing test track of the 2012 Mario AI championship: entries and evaluation. 2013 IEEE Conference on Computational Intelligence in Games (CIG), Niagara Falls, ON, Canada, 11-13 August, 2013. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/CIG.2013.6633634
2012
Journal Article
Using landscape topology to compare continuous metaheuristics: a framework and case study on EDAs and ridge structure
Morgan, R. and Gallagher, M. (2012). Using landscape topology to compare continuous metaheuristics: a framework and case study on EDAs and ridge structure. Evolutionary Computation, 20 (2), 277-299. doi: 10.1162/EVCO_a_00070
2012
Conference Publication
Game designers training first person shooter bots
McPartland, Michelle and Gallagher, Marcus (2012). Game designers training first person shooter bots. AI 2012: Advances in Artificial Intelligence, Sydney, Australia, 4 - 7 December 2012. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-35101-3_34
2012
Conference Publication
Beware the parameters: estimation of distribution algorithms applied to circles in a square packing
Gallagher, Marcus (2012). Beware the parameters: estimation of distribution algorithms applied to circles in a square packing. Parallel Problem Solving from Nature - PPSN XII 12th International Conference, Taormina, Italy, 1 - 5 September 2012. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-32964-7_48
2012
Conference Publication
Astronomical catalogue matching as a mixture model problem
Rohde, David, Gallagher, Marcus and Drinkwater, Michael (2012). Astronomical catalogue matching as a mixture model problem. 11th Brazilian Meeting on Bayesian Statistics (EBEB), Amparo, Brazil, 18-22 March 2012. College Park, MD, USA: American Institute of Physics. doi: 10.1063/1.4759615
2012
Journal Article
Introducing cloud computing topics in curricula
Chen, Ling, Liu, Yang, Gallagher, Marcus, Pailthorpe, Bernard, Sadiq, Shazia, Shen, Heng Tao and Li, Xue (2012). Introducing cloud computing topics in curricula. Journal of Information Systems Education, 23 (3), 315-324.
Funding
Supervision
Availability
- Associate Professor Marcus Gallagher is:
- Available for supervision
Before you email them, read our advice on how to contact a supervisor.
Supervision history
Current supervision
-
Doctor Philosophy
Adaptive Curriculums for Robotic Reinforcement Learning
Principal Advisor
-
Doctor Philosophy
Multi-objective optimisation and multi-agent learning for IoT devices.
Principal Advisor
Other advisors: Associate Professor Archie Chapman
-
Doctor Philosophy
Hybrid local/global optimisation for the design of diverse structures
Principal Advisor
-
Doctor Philosophy
Improving neuroevolution using ideas from deep learning and optimization
Principal Advisor
Other advisors: Associate Professor Archie Chapman
-
Doctor Philosophy
Improving neuroevolution using ideas from deep learning and optimization
Principal Advisor
Other advisors: Associate Professor Archie Chapman
-
Doctor Philosophy
Generating data-driven continuous optimization problems for benchmarking
Principal Advisor
Other advisors: Professor Brian Lovell
-
Doctor Philosophy
Digital simulation and model guided optimisation of light driven cell factories
Associate Advisor
Other advisors: Dr Juliane Wolf, Professor Ben Hankamer
-
Doctor Philosophy
Towards Autonomous Network Security
Associate Advisor
Other advisors: Associate Professor Marius Portmann, Dr Siamak Layeghy
-
Doctor Philosophy
Medical Image Segmentation with Limited Annotated Data
Associate Advisor
Other advisors: Professor Brian Lovell
-
Doctor Philosophy
Towards Autonomous Network Security
Associate Advisor
Other advisors: Dr Siamak Layeghy, Associate Professor Marius Portmann
-
Doctor Philosophy
Characterizing Influence and Sensitivity in the Interpolating Regime
Associate Advisor
Other advisors: Professor Fred Roosta
-
Master Philosophy
Forecasting and optimising decisions with machine learing
Associate Advisor
Other advisors: Dr Slava Vaisman
Completed supervision
-
2024
Doctor Philosophy
Fitness Landscape Features as Curriculum Ordering Measures for Reinforcement Learning
Principal Advisor
-
2023
Doctor Philosophy
Parsimony and Performance in Rule-Based Evolutionary Reinforcement Learning
Principal Advisor
-
2022
Doctor Philosophy
Discounting-free Policy Gradient Reinforcement Learning from Transient States
Principal Advisor
Other advisors: Professor Fred Roosta
-
2021
Master Philosophy
Stochaskell: A common platform for probabilistic programming research and applications
Principal Advisor
Other advisors: Dr Thomas Taimre
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2021
Doctor Philosophy
Improved Evaluation of Existing Methods in Landscape Analysis and Comparison of Black Box Optimization Problems using Regression Models
Principal Advisor
Other advisors: Dr Ian Wood
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2020
Doctor Philosophy
Results on Infinitely Wide Multi-layer Perceptrons
Principal Advisor
Other advisors: Professor Fred Roosta
-
2015
Doctor Philosophy
Analysing and Comparing Problem Landscapes for Black-Box Optimization via Length Scale
Principal Advisor
-
2015
Doctor Philosophy
Data-Driven Analysis of Variables and Dependencies in Continuous Optimization Problems and Estimation of Distribution Algorithms.
Principal Advisor
Other advisors: Dr Ian Wood
-
2014
Doctor Philosophy
Towards a Biologically Plausible Computational Model of Developmental Learning with Robotic Applications
Principal Advisor
-
2013
Doctor Philosophy
Training Bots to Play: Investigating Interactive Reinforcement Learning for Bot Behaviours in Shooter Games
Principal Advisor
-
2013
Doctor Philosophy
Advanced Computational Methods for System Voltage Stability Enhancement
Principal Advisor
-
2010
Master Philosophy
GMMEDA : A demonstration of probabilistic modelling in continuous metaheuristic optimization using mixture models
Principal Advisor
-
2010
Doctor Philosophy
Optimal active learning: experimental factors and membership query learning
Principal Advisor
Other advisors: Professor Janet Wiles
-
2009
Doctor Philosophy
The Development and Application of Statistical and Machine Learning Techniques in Probabilistic Astronomical Catalogue-Matching Problems
Principal Advisor
-
2009
Doctor Philosophy
Kinematic and Elasto-Dynamic Design Optimisation of a Class of Parallel Kinematic Machines
Principal Advisor
-
2006
Doctor Philosophy
TOWARDS IMPROVED EXPERIMENTAL EVALUATION AND COMPARISON OF EVOLUTIONARY ALGORITHMS
Principal Advisor
-
Doctor Philosophy
TOPOLOGICAL MODELS OF TRANSMEMBRANE PROTEINS FOR SUBCELLULAR LOCALIZATION PREDICTION
Principal Advisor
Other advisors: Professor Mikael Boden, Professor Geoffrey McLachlan
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2024
Doctor Philosophy
Investigating the use of Computer Vision Techniques for Analysing the Surf Zone and Swash Zone
Associate Advisor
Other advisors: Professor Tom Baldock
-
2024
Doctor Philosophy
Approaches to scalable, sustainable, and ethical natural language processing research in the face of rapid development
Associate Advisor
Other advisors: Professor Janet Wiles
-
2023
Doctor Philosophy
The Detection of Network Cyber Attacks Using Machine Learning
Associate Advisor
Other advisors: Dr Siamak Layeghy, Associate Professor Marius Portmann
-
2023
Master Philosophy
Graph Representation Learning for Cyberattack Detection and Forensics
Associate Advisor
Other advisors: Dr Siamak Layeghy, Associate Professor Marius Portmann
-
2022
Doctor Philosophy
Efficient second-order optimisation methods for large scale machine learning
Associate Advisor
Other advisors: Professor Fred Roosta
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2018
Doctor Philosophy
Smart Deployment of Community Energy Storage in Power Grid with PV Units
Associate Advisor
Other advisors: Professor Mithulan Nadarajah
-
2015
Master Philosophy
Multiple Instance Learning for Breast Cancer Magnetic Resonance Imaging
Associate Advisor
-
2015
Master Philosophy
Large Scale Material Science Data Analysis
Associate Advisor
Other advisors: Professor Helen Huang
-
2015
Doctor Philosophy
Biometric Markers for Affective Disorders
Associate Advisor
Other advisors: Professor Mikael Boden
-
2015
Doctor Philosophy
Multi-step forecasts of complex dynamical systems using soft-computing tools, with application to crude oil returns
Associate Advisor
-
2015
Doctor Philosophy
Making the most of machine learning and freely available datasets: A deforestation case study
Associate Advisor
Other advisors: Emeritus Professor Marc Hockings
-
2014
Doctor Philosophy
Machine Learning as an Adjunct to Clinical Decision Making in Alcohol Dependence Treatment
Associate Advisor
Other advisors: Professor Jason Connor
-
2014
Doctor Philosophy
Group-based Classification with an Application in Cervical Cancer Screening
Associate Advisor
-
2014
Doctor Philosophy
Estimation of Distribution Algorithms for Single- and Multi-Objective Optimization
Associate Advisor
Other advisors: Dr Ian Wood, Professor Dirk Kroese
-
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2008
Doctor Philosophy
Visual Learning for Mobile Robot Localisation
Associate Advisor
-
2008
Doctor Philosophy
Adaptation by prediction: Reading the play in robot soccer
Associate Advisor
-
2006
Doctor Philosophy
Implementing blind source separation in signal processing and telecommunications
Associate Advisor
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2005
Doctor Philosophy
THE NATURE OF CHANGE IN COMPLEX, SOCIO-TECHNICAL SYSTEMS
Associate Advisor
-
2005
Doctor Philosophy
Application of the Tree Augmented Naive Bayes Network to Classification and Forecasting
Associate Advisor
-
2004
Doctor Philosophy
FAST LEARNING IN BOLTZMANN MACHINES
Associate Advisor
Media
Enquiries
Contact Associate Professor Marcus Gallagher directly for media enquiries about:
- Artificial Intelligence
- Big Data
- Computer programming
- Data Science
- Evolutionary algorithms
- Evolutionary Computation
- Heuristic optimisation
- High-dimensional data - visualisation in computers
- Intelligent systems
- Machine learning
- Neural networks
- Optimisation Algorithms
- Search space analysis - IT
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