
Overview
Background
Jerzy Filar is Emeritus Professor of Applied Mathematics. Jerzy is a broadly trained applied mathematician with research interests spanning a spectrum of both theoretical and applied topics in Operations Research, Stochastic Modelling, Optimisation, Game Theory and Environmental Modelling. Professor Filar co-authored, or authored, five books or monographs and approximately 100 refereed research papers. He has a record of research grants/contracts with agencies and research institutes such as NSF, ARC, US EPA, World Resources Institute, DSTO, FRDC and the Sir Keith and Sir Ross Smith Foundation. He is editor-in-chief of Springer’s Environmental Modelling and Assessment and served on editorial boards of several other journals. He has supervised or co-supervised 29 PhD students. Jerzy's Erdos Number is 3.
Availability
- Emeritus Professor Jerzy Filar is:
- Available for supervision
Fields of research
Qualifications
- Bachelor (Honours) of Science (Advanced), University of Melbourne
- Masters (Coursework), Monash University
- Masters (Coursework), University of Illinois
- Doctor of Philosophy, University of Illinois
Research interests
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Stochastic Modelling
Markov Decision Processes, Stochastic Games, Risk.
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Analytic Perturbation Theory and Applications
Regular and singular perturbations of matrices and operators and their applications to optimisation and Markov chains.
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Operations Research and Optimisation
Linear, nonlinear and dynamic programming. Applications to patient flow modelling, airport recovery problem, electricity grid operations.
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Environmental Modelling
Sustainable fisheries, sustainability and the times scales conjecture, cascading errors in complex models of the environment, evolutionary games.
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Graph Theory
Hamiltonian cycle problem, spectral properties of regular graphs.
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Game Theory
Non-cooperative dynamic games, games with incompetent players, applications of game theory.
Research impacts
In his last role as CARM Director, Professor Filar and the team are partnered with Queensland’s Department of Agriculture and Fisheries (DAF) to equip their stock assessments with the very latest statistical and mathematical modelling methodologies to support the Sustainable Fisheries Strategy. As fisheries are not fully observable and fish numbers vary as they are lost to predators , disease, aging, fishing pressures and other environmental factors it is very challenging to devise reliable assessments and sustainable harvest levels that deliver economic benefits without dangerously depleting fish stocks. This is where mathematical and statistical modelling as well as computer simulations offer an effective and risk-free approach to estimate likely impacts of any proposed change.
Works
Search Professor Jerzy Filar’s works on UQ eSpace
2024
Journal Article
Overcoming the impossibility of age-balanced harvest
Filar, Jerzy A., Holden, Matthew H., Mendiolar, Manuela and Streipert, Sabrina H. (2024). Overcoming the impossibility of age-balanced harvest. Mathematical Biosciences, 367 109111, 1-11. doi: 10.1016/j.mbs.2023.109111
2023
Journal Article
Capturing episodic impacts of environmental signals
Mendiolar, M., Filar, J.A., Yang, W.-H., Leahy, S. and Courtney, A.J. (2023). Capturing episodic impacts of environmental signals. Environmental Modelling and Software, 170 105837, 1-19. doi: 10.1016/j.envsoft.2023.105837
2023
Journal Article
Multi-pass Bayesian estimation: a robust Bayesian method
Lei, Yeming, Zhou, Shijie, Filar, Jerzy and Ye, Nan (2023). Multi-pass Bayesian estimation: a robust Bayesian method. Computational Statistics, 39 (4), 2183-2216. doi: 10.1007/s00180-023-01390-0
2023
Conference Publication
Estimating recreational catch
Mendiolar, Manuela, Filar, Jerzy A., O'Neill, Michael F., Martin, Tyson, Teixeira, Daniella, Webley, James and Holden, Matthew (2023). Estimating recreational catch. 25th International Congress on Modelling and Simulation, Darwin, NT Australia, 9 to 14 July 2023. Canberra, ACT Australia: Modelling and Simulation Society of Australia and New Zealand. doi: 10.36334/modsim.2023.mendiolar
2023
Journal Article
Where Do Mistakes Lead? A Survey of Games with Incompetent Players
Graham, Thomas, Kleshnina, Maria and Filar, Jerzy A. (2023). Where Do Mistakes Lead? A Survey of Games with Incompetent Players. Dynamic Games and Applications, 13 (1), 231-264. doi: 10.1007/s13235-022-00425-3
2023
Journal Article
Empirical parameterisation and dynamical analysis of the allometric Rosenzweig-MacArthur equations
McKerral, Jody C., Kleshnina, Maria, Ejov, Vladimir, Bartle, Louise, Mitchell, James G. and Filar, Jerzy A. (2023). Empirical parameterisation and dynamical analysis of the allometric Rosenzweig-MacArthur equations. PLoS One, 18 (2) e0279838, 1-17. doi: 10.1371/journal.pone.0279838
2023
Journal Article
Hidden equations of risk critical thresholds
Ejov, Vladimir V., Filar, Jerzy A. and Qiao, Zhihao (2023). Hidden equations of risk critical thresholds. Stochastic Models, 39 (2), 383-413. doi: 10.1080/15326349.2022.2108452
2022
Journal Article
Shifts in evolutionary balance of phenotypes under environmental changes
Kleshnina, Maria, McKerral, Jody C., González-Tokman, Cecilia, Filar, Jerzy A. and Mitchell, James G. (2022). Shifts in evolutionary balance of phenotypes under environmental changes. Royal Society Open Science, 9 (11) 220744, 1-17. doi: 10.1098/rsos.220744
2022
Journal Article
Square root identities for harvested Beverton–Holt models
Filar, Jerzy and Streipert, Sabrina (2022). Square root identities for harvested Beverton–Holt models. Journal of Theoretical Biology, 549 111199, 1-14. doi: 10.1016/j.jtbi.2022.111199
2021
Journal Article
Mistakes can stabilise the dynamics of rock-paper-scissors games
Kleshnina, Maria, Streipert, Sabrina S., Filar, Jerzy A. and Chatterjee, Krishnendu (2021). Mistakes can stabilise the dynamics of rock-paper-scissors games. PLoS Computational Biology, 17 (4) e1008523, e1008523. doi: 10.1371/journal.pcbi.1008523
2020
Journal Article
Prioritised learning in snowdrift-type games
Kleshnina, Maria, Streipert, Sabrina S., Filar, Jerzy A. and Chatterjee, Krishnendu (2020). Prioritised learning in snowdrift-type games. Mathematics, 8 (11) 1945, 1-20. doi: 10.3390/math8111945
2020
Journal Article
Risk sensitivity in Beverton-Holt fishery with multiplicative harvest
Filar, Jerzy A., Qiao, Zhihao and Streipert, Sabrina (2020). Risk sensitivity in Beverton-Holt fishery with multiplicative harvest. Natural Resource Modeling, 33 (3) e12257. doi: 10.1111/nrm.12257
2020
Journal Article
Hamiltonian Cycles and Subsets of Discounted Occupational Measures
Eshragh, Ali, Filar, Jerzy A., Kalinowski, Thomas and Mohammadian, Sogol (2020). Hamiltonian Cycles and Subsets of Discounted Occupational Measures. Mathematics of Operations Research, 45 (2), 713-731. doi: 10.1287/moor.2019.1009
2020
Journal Article
Hospital’s instability wedges
Ben-Tovim, David, Bogomolov, Tim, Filar, Jerzy, Hakendorf, Paul, Qin, Shaowen and Thompson, Campbell (2020). Hospital’s instability wedges. Health Systems, 9 (3), 202-211. doi: 10.1080/20476965.2018.1524407
2019
Book Chapter
Postponing Collapse: Ergodic Control with a Probabilistic Constraint
Borkar, Vivek S. and Filar, Jerzy A. (2019). Postponing Collapse: Ergodic Control with a Probabilistic Constraint. Modeling, Stochastic Control, Optimization, and Applications. (pp. 57-65) edited by Yin, G. and Zhang, Q.. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-25498-8_3
2019
Conference Publication
POMDPs for sustainable fishery management
Filar, Jerzy A., Qiao, Zhihao and Ye, Nan (2019). POMDPs for sustainable fishery management. International Congress on Modelling and Simulation, Canberra, Australia, 1-6 December 2019. Modelling and Simulation Society of Australia and New Zealand. doi: 10.36334/modsim.2019.g2.filar
2018
Journal Article
Foreword
Filar, Jerzy A. (2018). Foreword. Environmental Modeling and Assessment, 23 (6), 609-610. doi: 10.1007/s10666-018-9645-z
2018
Journal Article
Linearly-growing reductions of Karp's 21 NP-complete problems
Filar, Jerzy, Haythorpe, Michael and Taylor, Richard (2018). Linearly-growing reductions of Karp's 21 NP-complete problems. Numerical Algebra, Control and Optimization, 8 (1), 1-16. doi: 10.3934/naco.2018001
2018
Journal Article
Evolutionary games under incompetence
Kleshnina, Maria, Filar, Jerzy A., Ejov, Vladimir and McKerral, Jody C. (2018). Evolutionary games under incompetence. Journal of Mathematical Biology, 77 (3), 627-646. doi: 10.1007/s00285-018-1221-2
2017
Journal Article
A note on using the resistance-distance matrix to solve Hamiltonian cycle problem
Ejov, V., Filar, J. A., Haythorpe, M., Roddick, J. F. and Rossomakhine, S. (2017). A note on using the resistance-distance matrix to solve Hamiltonian cycle problem. Annals of Operations Research, 261 (1-2), 393-399. doi: 10.1007/s10479-017-2571-7
Funding
Past funding
Supervision
Availability
- Emeritus Professor Jerzy Filar is:
- Available for supervision
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Available projects
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Risk and Uncertainty Quantification in Environmental Modelling
Mathematical models of environmental problems often demand understanding of complex dynamics and interactions between many physical and biological variables on the one hand, and human inputs on the other. Uncertainties accompanying such models stem from multiple sources. Sometimes they manifest themselves as cascading errors and at other times they involve the risk of key variables crossing undesirable thresholds. In both cases they undermine confidence in either the model or, worse still, the underlying science.
The accompanying mathematical problems can be studied using a wide range of approaches including (but not limited to) perturbation theory, stochastic processes, partially observable Markov decision processes, statistical methods, dynamical systems and simulation. They can also be applied in several important contexts including (but not limited to) conservation of natural resources, optimizing harvests of fish subject to sustainability constraints or generating warning signals for species whose abundance drops to low levels. One particularly challenging problem is that of designing controls that minimize the probability of a catastrophe, consistently over time, while achieving satisfactory and sustainable resource consumption. A related problem, also stemming from fishery science applications, is that of devising a “balanced harvest” strategy that ultimately restores the proportions of age cohorts of the harvested species to those that are natural for that species.
There are several PhD, Masters’ or Honours’ research projects that can be designed on this general theme and tailored to the particular student’s background and interests. For some projects co-supervision with scientists from the Queensland Department of Agriculture and Fisheries, or CSIRO may be required.
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Fishery-dependent monitoring of Queensland's fisheries
Review and evaluate efficient sampling programs: Is the right amount of sampling occurring for each species? Are there any significant biases in the sampling programs for each species? Assess whether routine analyses are being carried out correctly and to develop new analyses for fisheries management.
Project components include developing: Quantitative analyses to optimise fishery-dependent sampling across multiple species and regions. Routine methods for assessing precision of current sampling of fish length and age. New methods for turning fish length and age data into advice (indicators) about fishing pressure and the status of fish stocks. A corresponding harvest strategy and reference points for judging the performance of the indicators.
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Queensland state-wide estimation of recreational fish catches
Improved estimation of state-wide recreational harvests, including resampling, bootstrap and MCMC techniques. Quantify changes in survey angler avidity and recall bias between survey years and methodologies; adjust previous survey data to obtain improved estimates. Evaluating sampling frames - develop methods to generate state-wide harvest estimates (and associated measures of uncertainty) from several synchronous samples taken from different sampling frames (e.g. a licence frame and a residential telephone number list). Develop hierarchical and conditional mixed models for estimation of recreational fish catch and catch rates. Investigate the statistical modelling of recreational survey data collected from multiple survey methods.
From survey to analysis: dealing with differences in the scale at which survey data are collected and the scale at which data are analysed. Examine appropriate estimation methods for different fish species. Develop statistical methods for low fish abundance or recreational species caught by ‘hard-to-reach’ fishers. Develop methods to engage and retain recreational fishers in volunteer data contribution programs.
Supervision history
Current supervision
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Doctor Philosophy
Machine Learning for Quantitative Fisheries Stock Assessments
Associate Advisor
Other advisors: Dr Nan Ye
Completed supervision
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2024
Doctor Philosophy
Parametric sensitivity of threshold risk and multi-absorption phase type distributions
Principal Advisor
Other advisors: Associate Professor Yoni Nazarathy
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2019
Doctor Philosophy
Evolutionary games under incompetence & foraging strategies of marine bacteria
Principal Advisor
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2024
Doctor Philosophy
On quantitative indices and modelling of harvested fish populations
Associate Advisor
Other advisors: Dr Matthew Holden
Media
Enquiries
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