![Associate Professor Marcus Gallagher](/sites/default/files/profiles/469.jpeg)
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
2007
Journal Article
Combining meta-EAs and racing for difficult EA parameter tuning tasks
Yuan, Bo and Gallagher, Marcus (2007). Combining meta-EAs and racing for difficult EA parameter tuning tasks. Studies in Computational Intelligence, 54, 121-142. doi: 10.1007/978-3-540-69432-8_6
2007
Conference Publication
Evolving pac-man players: Can we learn from raw input?
Gallagher, M. and Ledwich, M. (2007). Evolving pac-man players: Can we learn from raw input?. 2007 IEEE Symposium Series on Computational Intelligence and Games (IEEE SSCI 2007), Honolulu, Hawaii, 1-5 April, 2007. United States: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/CIG.2007.368110
2007
Conference Publication
An agent based approach to examining shared situation awareness
Connelly, S., Lindsay, P. A. and Gallagher, M. (2007). An agent based approach to examining shared situation awareness. 12th IEEE International Conference on Engineering Complex Computer Systems (ICECCS 2007), Auckland, New Zealand, 11-14 July 2007. Los Alamitos, CA, U.S.A.: IEEE Computer Society. doi: 10.1109/ICECCS.2007.14
2007
Conference Publication
A comparison of sequence kernels for localization prediction of transmembrane proteins
Maetschke, S., Gallagher, M. and Boden, M. (2007). A comparison of sequence kernels for localization prediction of transmembrane proteins. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology 2007 (CIBCB 2007), Honolulu, Hawaii, 1-5 April 2007. Piscataway, NJ, U.S.A.: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/cibcb.2007.4221246
2007
Book Chapter
Combining Meta-EAs and Racing for Difficult EA Parameter Tuning Tasks
Yuan, B. and Gallagher, M. (2007). Combining Meta-EAs and Racing for Difficult EA Parameter Tuning Tasks. Parameter Setting in Evolutionary Algorithms. (pp. 121-142) edited by Lobo, F. G., Lima, C. F. and Michalewicz, Z.. Berlin, Heidelberg, Germany: Springer-Verlag. doi: 10.1007/978-3-540-69432-8_6
2007
Journal Article
Parameter interdependence and uncertainty induced by lumping in a hydrologic model
Gallagher, MR and Doherty, J (2007). Parameter interdependence and uncertainty induced by lumping in a hydrologic model. Water Resources Research, 43 (5) W05421. doi: 10.1029/2006WR005347
2007
Conference Publication
Bayesian inference in estimation of distribution algorithms
Gallagher, M. R., Wood, I., Keith, J. and Sofronov, G. (2007). Bayesian inference in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation (CEC 2007), Singapore, 25-28 September 2007. Piscataway, NJ, U.S.A.: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/CEC.2007.4424463
2007
Conference Publication
Combining Meta-EAs and racing for difficult EA parameter tuning tasks
Yuan, Bo and Gallagher, Marcus (2007). Combining Meta-EAs and racing for difficult EA parameter tuning tasks. Workshop on Parameter Setting in Genetic and Evolutionary Algorithms, Washington Dc, 2005. BERLIN: SPRINGER-VERLAG BERLIN.
2006
Conference Publication
A mathematical modelling technique for the analysis of the dynamics of a simple continuous EDA
Yuan, Bo and Gallagher, Marcus (2006). A mathematical modelling technique for the analysis of the dynamics of a simple continuous EDA. 2006 IEEE Congress on Evolutionary Computation, CEC 2006, , , July 16, 2006-July 21, 2006.
2006
Journal Article
Introduction
Yin, Hujun, Gallagher, Marcus and Magdon-Ismail, Malik (2006). Introduction. International Journal of Neural Systems, 16 (5), v-vi.
2006
Edited Outputs
International Journal of Neural Systems
International Journal of Neural Systems. (2006). 16 (5)
2006
Journal Article
Matching of catalogues by probabilistic pattern classification
Rohde, D. J., Gallagher, M. R., Drinkwater, M. J. and Pimbblet, K. A. (2006). Matching of catalogues by probabilistic pattern classification. Monthly Notices of The Royal Astronomical Society, 369 (1), 2-14. doi: 10.1111/j.1365-2966.2006.10304.x
2006
Journal Article
A general-purpose tunable landscape generator
Gallagher, Marcus and Yuan, Bo (2006). A general-purpose tunable landscape generator. IEEE Transactions On Evolutionary Computation, 10 (5), 590-603. doi: 10.1109/TEVC.2005.863628
2006
Conference Publication
A mathematical modelling technique for the analysis of the dynamics of a simple continuous EDA
Gallagher, M. R. and Yuan, B. (2006). A mathematical modelling technique for the analysis of the dynamics of a simple continuous EDA. 2006 IEEE Congress on Evolutionary Computation (CEC 2006), Vancouver, Canada, 16-21 July 2006. Piscataway, NJ, U.S.A.: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/CEC.2006.1688497
2006
Conference Publication
Higher order HMMs for localization prediction of transmembrance proteins
Maetschke, S. R., Boden, M B and Gallagher, M R (2006). Higher order HMMs for localization prediction of transmembrance proteins. 2006 Workshop on Intelligent Systems for Bioinformatics (WISB 2006), Hobart, Australia, 4 December, 2006. New South Wales, Australia: Australian Computer Society Inc..
2005
Conference Publication
A hybrid approach to parameter tuning in genetic algorithms
Yuan, Bo and Gallagher, Marcus (2005). A hybrid approach to parameter tuning in genetic algorithms. 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005, , , September 2, 2005-September 5, 2005.
2005
Conference Publication
Experimental results for the special session on real-parameter optimization at CEC 2005: A simple, continuous EDA
Yuan, Bo and Gallagher, Marcus (2005). Experimental results for the special session on real-parameter optimization at CEC 2005: A simple, continuous EDA. 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005, , , September 2, 2005-September 5, 2005.
2005
Journal Article
Lecture Notes in Computer Science: Preface
Gallagher, Marcus, Hogan, James and Maire, Frederic (2005). Lecture Notes in Computer Science: Preface. Lecture Notes in Computer Science, 3578
2005
Other Outputs
McCulloch-Pitts Network
Gallagher, M. R. (2005). McCulloch-Pitts Network.
2005
Edited Outputs
Intelligent Data Engineering and Automated Learning - IDEAL2005
Marcus Gallagher, James Hogan and Frederic Maire eds. (2005). Intelligent Data Engineering and Automated Learning - IDEAL2005. 6th International Conference on Intelligent Data Engineering and Automated Learning - IDEAL 2005: Lecture Notes in Computer Science (journal), Brisbane, Australia, 6-8 July 2005. Germany: Springer.
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
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Doctor Philosophy
Hybrid local/global optimisation for the design of diverse structures
Principal Advisor
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Doctor Philosophy
Improving neuroevolution using ideas from deep learning and optimization
Principal Advisor
Other advisors: Associate Professor Archie Chapman
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Doctor Philosophy
Generating data-driven continuous optimization problems for benchmarking
Principal Advisor
Other advisors: Professor Brian Lovell
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Doctor Philosophy
Adaptive Curriculums for Robotic Reinforcement Learning
Principal Advisor
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Doctor Philosophy
Multi-objective optimisation and multi-agent learning for IoT devices.
Principal Advisor
Other advisors: Associate Professor Archie Chapman
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Doctor Philosophy
Characterizing Influence and Sensitivity in the Interpolating Regime
Associate Advisor
Other advisors: Professor Fred Roosta
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Master Philosophy
Forecasting and optimising decisions with machine learing
Associate Advisor
-
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
Completed supervision
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2024
Doctor Philosophy
Fitness Landscape Features as Curriculum Ordering Measures for Reinforcement Learning
Principal Advisor
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2023
Doctor Philosophy
Parsimony and Performance in Rule-Based Evolutionary Reinforcement Learning
Principal Advisor
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2022
Doctor Philosophy
Discounting-free Policy Gradient Reinforcement Learning from Transient States
Principal Advisor
Other advisors: Professor Fred Roosta
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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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2021
Master Philosophy
Stochaskell: A common platform for probabilistic programming research and applications
Principal Advisor
Other advisors: Dr Thomas Taimre
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2020
Doctor Philosophy
Results on Infinitely Wide Multi-layer Perceptrons
Principal Advisor
Other advisors: Professor Fred Roosta
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2015
Doctor Philosophy
Analysing and Comparing Problem Landscapes for Black-Box Optimization via Length Scale
Principal Advisor
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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
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2014
Doctor Philosophy
Towards a Biologically Plausible Computational Model of Developmental Learning with Robotic Applications
Principal Advisor
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2013
Doctor Philosophy
Training Bots to Play: Investigating Interactive Reinforcement Learning for Bot Behaviours in Shooter Games
Principal Advisor
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2013
Doctor Philosophy
Advanced Computational Methods for System Voltage Stability Enhancement
Principal Advisor
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2010
Master Philosophy
GMMEDA : A demonstration of probabilistic modelling in continuous metaheuristic optimization using mixture models
Principal Advisor
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2010
Doctor Philosophy
Optimal active learning: experimental factors and membership query learning
Principal Advisor
Other advisors: Professor Janet Wiles
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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
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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
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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
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2023
Doctor Philosophy
The Detection of Network Cyber Attacks Using Machine Learning
Associate Advisor
Other advisors: Dr Siamak Layeghy, Associate Professor Marius Portmann
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2023
Master Philosophy
Graph Representation Learning for Cyberattack Detection and Forensics
Associate Advisor
Other advisors: Dr Siamak Layeghy, Associate Professor Marius Portmann
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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
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2015
Master Philosophy
Multiple Instance Learning for Breast Cancer Magnetic Resonance Imaging
Associate Advisor
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2015
Master Philosophy
Large Scale Material Science Data Analysis
Associate Advisor
Other advisors: Professor Helen Huang
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2015
Doctor Philosophy
Biometric Markers for Affective Disorders
Associate Advisor
Other advisors: Professor Mikael Boden
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2015
Doctor Philosophy
Multi-step forecasts of complex dynamical systems using soft-computing tools, with application to crude oil returns
Associate Advisor
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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
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2014
Doctor Philosophy
Machine Learning as an Adjunct to Clinical Decision Making in Alcohol Dependence Treatment
Associate Advisor
Other advisors: Professor Jason Connor
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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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2014
Doctor Philosophy
Group-based Classification with an Application in Cervical Cancer Screening
Associate Advisor
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2008
Doctor Philosophy
Adaptation by prediction: Reading the play in robot soccer
Associate Advisor
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2008
Doctor Philosophy
Visual Learning for Mobile Robot Localisation
Associate Advisor
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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
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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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