Dr Luke Mathieson

Dr Luke Mathieson

Research Associate

School of Elect Engineering and Computer Science

It all adds up

Pairing powerful computer technology with applied mathematics, Dr Luke Mathieson's data analyses are a welcome, revolutionary step toward personalised patient care.

Luke Mathieson

Crunching numbers isn't for everyone. For Dr Luke Mathieson though, it's a gratifying challenge. The enthusiastic computer scientist is both a calculator and interpreter at the University of Newcastle's Centre for Information-Based Medicine (CIBM), approaching complex questions from novel algorithmic perspectives.

"I extract meaning from really big data sets," he explains.

"These sets are basically a bunch of figures in a file that tell you how molecular components interact."

"My job is to build networks to examine the links between them, with the eventual aim of pinpointing disease-related subtypes."

Consequently aiding the identification of key biomarkers capable of tracking – and perhaps blocking – the progression of cancer and neurodegeneration, Luke's studies are rapidly transforming multiple medical fields. Drawing together a number of clinical and academic disciplines, they're also an exciting new frontier where 'bench to bedside' research is concerned.

"The work I do is largely theoretical, but it has some very practical, 'real world' applications too," he affirms.

"We're looking to develop patient-tailored treatments for a host of conditions that are influenced by genetic aspects, for example, such as melanoma and schizophrenia."

It's classified

Luke began his research career with an Honours Degree at the University of Newcastle in 2004. Focusing on a "very small slice" of statistical database security, the 12-month investigation looked to balance a universal trade-off between access and privacy.

"My project was essentially about merging or masking sensitive information in such a way that ensures the databases you get at the end are still useable."

"Unfortunately though, I found that even if you take a very simple theoretical model, you can't prevent attacks without rendering them completely useless."

"Protecting files is therefore an almost impossible aim – if they're open to legitimate use, they're similarly open to illegitimate misuse."

Out of the 'too hard' basket

Decisively switching areas after completing his undergraduate program at the end of 2004, Luke opted to undertake several assignments on complexity theory with Professor Pablo Moscato. Equally impressed by the University's invention of an offshoot, known as parameritised complexity, Luke found a home for his research ambitions at the CIBM for the next two years.

"Our main goal was to find structure in data," he shares.

"The patterns we discovered were later used to produce sensible calculations."

Duly inspiring a global reexamination of problems once thought to be unsolvable, these studies led into Luke's PhD work at England's Durham University in 2007.

"During this time I developed a series of algorithms for some related complications in graph-editing," he reveals.

"Graphs are the mathematical term for networks."

"If you draw them on paper, which we often do, they're a bunch of circles and lines."

"The circles model things, like proteins or genes, and the lines represent their interactions."

Though comically admitting his candidature "probably sounds incredibly boring" to most people, Luke concedes he unearthed a whole set of interesting problems that are "really hard but not impossible" to crack during the three-year probe.

"With each graph, we have a small set of properties that we're wanting to satisfy," Luke describes.

"So vertices and edges have to be added and/or removed to make them fit."

"These graphs are then given to computers as inputs, telling them to do certain steps and generate a 'hopefully' predetermined product or result."

"Some are easy to produce algorithms for, meaning we can get computers to solve the problems correctly and quickly without using many resources, and others are not so easy."

Old and new

Luke returned to Australia after receiving his award, collaborating with Pablo for another year before moving to Macquarie University in 2011. The esteemed mathematician continued to worked on parameritised complexity throughout the three-year posting, combining it with dynamic graph theory to model a handful of mobile ad hoc networks.

"These are the sort you get from our phones and cars and computers talking to each other," he enlightens. 

"Each has a circle, but the lines and edges and vertices that connect them are constantly moving."

"This causes quite dramatic changes in the practice of our graphs."

Seeking to use maths in fresh and fascinating ways, Luke also undertook some "interesting guess work" to characterise pairwise relations between the devices.

"It looks very ugly to the public," he admits.

"All of a sudden some of the old algorithms that you used to use don't work anymore, so you're forced to come up with new ones."

Twice the trouble, twice the fun

Luke expanded this niche after returning to Newcastle in 2015, developing a practice called 'network alignment.' This time working with two or more networks, he is looking to detect a series of intricate sub-networks common in multiple species. 

"What we want to do is line them up so that all the circles, edges and vertices map to each other," he states.

"If they line up well, this tells us that they share a very similar structure."

"For example, if you take the protein-protein interactions of a well-studied organism, like a nematode worm, and line them up with the human protein-protein interactions, we can figure out the basic biological mechanisms each is controlling."

Disclosing his long-term goal of automating this process "as much as possible" for personalised drug therapy, Luke advises that the same can be said for healthy and unhealthy human networks.

"If we can identify the proteins that are doing funny things, we can start to create a targeted approach," he suggests.

"This would be much more effective than chemotherapy, for instance, which kills the patient almost as quickly as it kills the cancer."

Super skills

A master at multitasking, Luke is also currently exploring 'super networks.' Employed to do so under an Australian Research Council Discovery Project Grant, he is applying innovative mathematical techniques to build alignments that satisfy a number of different criteria.

"These networks will tell us how protein and gene data interact, or how a disease progresses," he insists.

"But it's not a simple task – we're hoping to make them information-rich and this requires more than just nodes and lines." 

"Super networks are really a whole bunch of individual networks put together."

"Each is about 200GB, which is seriously pushing the limits of what you can do with a computer."

With parallel computation, a form of computation in which many calculations are carried out simultaneously, making it easier and quicker than ever before to "do something sensible" with such datasets, Luke and his colleagues are well on their way to achieving what was once deemed impossible.   

"Large problems can often be divided into smaller ones, which are then solved at the same time," he elucidates.

"We're finally getting to the point where we can disentangle them and extract meaningful biological and medical information."

It all adds up

It all adds up Pairing powerful computer technology with applied mathematics, Dr Luke Mathieson’s data analyses are a welcome, revolutionary step toward persona

Read more

Career Summary


  • Doctor of Philosophy, University of Durham
  • Bachelor of Science, University of Newcastle
  • Bachelor of Computer Science, University of Newcastle
  • Bachelor of Computer Science (Honours), University of Newcastle


  • Algorithmics
  • Bioinformatics
  • Combinatorics
  • Computational Complexity
  • Data Structures
  • Discrete Mathematics
  • Graph Theory
  • Object Oriented Programming
  • Parameterized Complexity
  • Programming Language Theory
  • Software Engineering
  • Theory of Computation


  • English (Mother)

Fields of Research

Code Description Percentage
080201 Analysis of Algorithms and Complexity 50
080202 Applied Discrete Mathematics 30
080301 Bioinformatics Software 20

Professional Experience

UON Appointment

Title Organisation / Department
Research Associate University of Newcastle
School of Elect Engineering and Computer Science

Academic appointment

Dates Title Organisation / Department
1/01/2014 - 1/09/2014 Adjunct Lecturer Macquarie University
Department of Computing
1/05/2011 - 1/12/2013 Postdoctoral Research Fellow Macquarie University
Department of Computing
1/01/2010 - 1/05/2011 Postdoctoral Research Associate University of Newcastle
Centre for Information-Based Medicine


For publications that are currently unpublished or in-press, details are shown in italics.

Journal article (11 outputs)

Year Citation Altmetrics Link
2017 Mathieson L, Mendes A, Marsden J, Pond J, Moscato P, 'Computer-Aided Breast Cancer Diagnosis with Optimal Feature Sets: Reduction Rules and Optimization Techniques.', Methods Mol Biol, 1526 299-325 (2017)
DOI 10.1007/978-1-4939-6613-4_17
Co-authors Alexandre Mendes, Pablo Moscato
2016 Mathieson L, Luccio F, Mans B, Pagli L, 'Complete Balancing via Rotation', The Computer Journal, (2016)
DOI 10.1093/comjnl/bxw018
2016 Mathieson L, 'Synergies in critical reflective practice and science: Science as reflection and reflection as science', Journal of University Teaching & Learning Practice, 13 (2016) [C1]
2016 Konyagin SV, Luca F, Mans B, Mathieson L, Sha M, Shparlinski IE, 'Functional graphs of polynomials over finite fields', Journal of Combinatorial Theory, Series B, 116 87-122 (2016)
DOI 10.1016/j.jctb.2015.07.003
2015 Frati F, Gaspers S, Gudmundsson J, Mathieson L, 'Augmenting Graphs to Minimize the Diameter', Algorithmica, 72 995-1010 (2015)
DOI 10.1007/s00453-014-9886-4
2014 Mans B, Mathieson L, 'On the treewidth of dynamic graphs', Theoretical Computer Science, 554 217-228 (2014)
DOI 10.1016/j.tcs.2013.12.024
2012 Mathieson L, Szeider S, 'Editing graphs to satisfy degree constraints: A parameterized approach', Journal of Computer and System Sciences, 78 179-191 (2012) [C1]
Citations Scopus - 23Web of Science - 16
2012 Arefin AS, Mathieson L, Johnstone DM, Berretta RE, Moscato PA, 'Unveiling clusters of RNA transcript pairs associated with markers of Alzheimer's disease progression', PLOS One, 7 1-25 (2012) [C1]
Citations Scopus - 17Web of Science - 16
Co-authors Pablo Moscato, Regina Berretta
2010 Mellor D, Prieto-Rodriguez E, Mathieson L, Moscato PA, 'A kernelisation approach for multiple d-hitting set and its application in optimal multi-drug therapeutic combinations', Plos One, 5 1-13 (2010) [C1]
DOI 10.1371/journal.pone.0013055
Citations Scopus - 5Web of Science - 3
Co-authors Elena Prieto, Pablo Moscato
2010 Rizzi R, Mahata P, Mathieson L, Moscato PA, 'Hierarchical clustering using the arithmetic-harmonic cut: Complexity and experiments', Plos One, 5 1-8 (2010) [C1]
DOI 10.1371/journal.pone.0014067
Citations Scopus - 2Web of Science - 1
Co-authors Pablo Moscato
2010 Mathieson L, 'The parameterized complexity of editing graphs for bounded degeneracy', Theoretical Computer Science, 411 3181-3187 (2010)
DOI 10.1016/j.tcs.2010.05.015
Show 8 more journal articles

Conference (9 outputs)

Year Citation Altmetrics Link
2016 de Vries NJ, Arefin AS, Mathieson L, Lucas B, Moscato P, 'Relative neighborhood graphs uncover the dynamics of social media engagement', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2016)

© Springer International Publishing AG 2016.In this paper, we examine if the Relative Neighborhood Graph (RNG) can reveal related dynamics of page-level social media metrics. A s... [more]

© Springer International Publishing AG 2016.In this paper, we examine if the Relative Neighborhood Graph (RNG) can reveal related dynamics of page-level social media metrics. A statistical analysis is also provided to illustrate the application of the method in two other datasets (the Indo-European Language dataset and the Shakespearean Era Text dataset). Using social media metrics on the world¿s ¿top check-in locations¿ Facebook pages dataset, the statistical analysis reveals coherent dynamical patterns. In the largest cluster, the categories ¿Gym¿, ¿Fitness Center¿, and ¿Sports and Recreation¿ appear closely linked together in the RNG. Taken together, our study validates our expectation that RNGs can provide a ¿parameterfree¿ mathematical formalization of proximity. Our approach gives useful insights on user behaviour in social media page-level metrics as well as other applications.

DOI 10.1007/978-3-319-49586-6_19
Co-authors Pablo Moscato
2013 Mathieson L, Mans B, 'On the Treewidth of Dynamic Graphs', Computing and Combinatorics (2013)
DOI 10.1007/978-3-642-38768-5_32
2013 Mathieson L, Frati F, Gaspers S, Gudmundsson J, 'Augmenting Graphs to Minimize the Diameter', Algorithms and Computation (2013)
DOI 10.1007/978-3-642-45030-3_36
2011 Arefin AS, Inostroza-Ponta M, Mathieson L, Berretta RE, Moscato PA, 'Clustering nodes in large-scale biological networks using external memory algorithms', Algorithms and Architectures for Parallel Processing (2011) [E1]
DOI 10.1007/978-3-642-24669-2_36
Citations Scopus - 5Web of Science - 6
Co-authors Regina Berretta, Pablo Moscato
2010 Mellor D, Prieto-Rodriguez E, Mathieson L, Moscato PA, 'Uncovering combinations: Using graph theory to find multi-drug therapies', Biomarker Discovery Conference. Poster Program (2010) [E3]
Co-authors Pablo Moscato, Elena Prieto
2008 Mathieson L, Szeider S, 'Parameterized Graph Editing with Chosen Vertex Degrees', Combinatorial Optimization and Applications (2008)
DOI 10.1007/978-3-540-85097-7_2
2005 Moscato PA, Mathieson L, Mendes ADS, Berretta RE, 'The Electronic Primaries: Predicting the U.S. Presidency Using Feature Selection with Safe Data Reduction', Proceedings of the twenty eighth Australasian Computer Science Conference (ACSC 2005) Newcastle, Australia, January, 2005 (2005) [E1]
Citations Scopus - 1
Co-authors Pablo Moscato, Alexandre Mendes, Regina Berretta
2004 Mathieson L, King T, Brankovic L, '2-Compromise: usability in 1-dimensional statistical database', Proceedings from Fifteenth Australasian Workshop on Combinatorial Algorithms (2004) [E1]
Co-authors Ljiljana Brankovic
2004 Mathieson L, Prieto-Rodriguez E, Shaw PE, 'Packing edge disjoint triangles: a parameterized view', Parameterized and Exact Computation (2004) [E1]
Citations Scopus - 16Web of Science - 23
Co-authors Elena Prieto
Show 6 more conferences

Thesis / Dissertation (1 outputs)

Year Citation Altmetrics Link
2010 Mathieson L, The Parameterized Complexity of Degree Constrained Editing Problems, University of Durham (2010)

Grants and Funding


Number of grants 3
Total funding $64,550

Click on a grant title below to expand the full details for that specific grant.

20162 grants / $14,550

Multi-objective Memetic Algorithm for Large-Scale Community Detection Considering both Topology and Contents$10,000

‘Community Detection’ that aims to group densely connected/correlated nodes of a network, is one of the most challenging and central problems in the field of network analysis. The emergence of gigantic networks in biology, social media, and business is now greatly challenging the performance of state-of-the-art algorithms for community detection. Association of different types of contents in these networks is increasing their complexity and necessitates more sophisticated detection of communities. This project will develop memetic computing techniques to address these needs. We will introduce new mathematical models that take into consideration both the links and content information of each network node. Our work will deliver highly efficient and intelligent computational solutions for large networks. The project will lead to the future of smart information analytics for networks with millions of nodes. We will develop sophisticated methods for community detection of wide applicability in biology, social sciences, engineering and the knowledge economy.

Funding body: University of Newcastle - Faculty of Engineering & Built Environment

Funding body University of Newcastle - Faculty of Engineering & Built Environment
Project Team

Regina Berretta, Nasimul Noman, Pablo Moscato, Luke Mathieson

Scheme Pilot Grant
Role Investigator
Funding Start 2016
Funding Finish 2016
Type Of Funding Internal
Category INTE

International Partnership Encouragement Grant$4,550

Funding body: University of Newcastle - Faculty of Engineering & Built Environment

Funding body University of Newcastle - Faculty of Engineering & Built Environment
Project Team

Luke Mathieson

Scheme Travel Grant
Role Lead
Funding Start 2016
Funding Finish 2016
Type Of Funding Internal
Category INTE

20111 grants / $50,000

Computational prediction and functional clarification of novel drug combination strategies for the treatment of brain tumours$50,000

Funding body: Maitland Cancer Appeal Committee

Funding body Maitland Cancer Appeal Committee
Project Team Professor Pablo Moscato, Dr DAN Johnstone, Associate Professor Regina Berretta, Doctor Luke Mathieson, Professor Manuel Graeber, Doctor Jennette Sakoff
Scheme Research Project
Role Investigator
Funding Start 2011
Funding Finish 2011
GNo G1100275
Type Of Funding Donation - Aust Non Government
Category 3AFD

Dr Luke Mathieson


Research Associate
School of Elect Engineering and Computer Science
Faculty of Engineering and Built Environment

Contact Details

Email luke.mathieson@newcastle.edu.au
Phone (02) 40420832


Room Level 3 Pod
Building HMRI Building
Location 1 Kookaburra Circuit, John Hunter Hospital