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Professor Peter Taylor
ACEMS Director, Chief Investigator
The University of Melbourne
Peter Taylor received a BSc(Hons) and a PhD in Applied Mathematics from the University of Adelaide in 1980 and 1987 respectively. In between, he spent time working for the Australian Public Service in Canberra. After periods at the Universities of Western Australia and Adelaide, he moved at the beginning of 2002 to the University of Melbourne. In January 2003, he took up a position as the inaugural Professor of Operations Research. He was Head of the Department of Mathematics and Statistics from 2005 until 2010.
Peter's research interests lie in the fields of stochastic modelling and applied probability, with particular emphasis on applications in telecommunications, biological modelling, healthcare, economics and disaster management. Recently he has become interested in the interaction of stochastic modelling with optimisation and optimal control under conditions of uncertainty. He is regularly invited to present plenary papers at international conferences. He has also acted on organising and program committees for many conferences.
Peter is the editor-in-chief of the Applied Probability Trust journals Journal of Applied Probability and Advances in Applied Probability and was the Editor-in-Chief of Stochastic Models between 2002 and 2018. He is also a member of the editorial board of Queueing Systems. He served on the Awards Committee of the Applied Probability Section of the Institute for Operations Research and Management Science (INFORMS) from 2005-2007 and in 2016 was Co-Chair of the Committee for the Nicholson Prize, awarded for the best student paper in operations research.
From 2006 to 2008, Peter was Chair of the Australia and New Zealand Division of Industrial and Applied Mathematics (ANZIAM), and from 2010 to 2012 he was the President of the Australian Mathematical Society. In 2013 he was awarded a Laureate Fellowship by the Australian Research Council, and in 2016 he became Director of ACEMS. In 2017, he was awarded the Ren Potts Medal by the Australian Society for Operations Research and in 2018 the George Szekeres Medal by the Australian Mathematical Society. Both medals are for career achievement.
Research Interests:
Complex Networks
Markov decision process
Matrix-analytic methods
Mechanism Design
Modelling of biological and environmental systems
Modelling of epidemics
Modelling of telecommunications systems
Optimisation and control
Parameter estimation
Queueing theory
Stochastic modelling
Projects
Publications
Book Chapters
Fackrell, M., & Taylor P.
(2017). Allocation in a vertical rotary car park.
(Boucherie, R. J., & van Dijk N. M., Ed.).Markov Decision Processes in Practice. 248, 337-370. doi: 10.1007/978-3-319-47766-4_12
Invited talks, refereed proceedings and other conference outputs
Niknami, B., & Taylor P.
(2019). Modelling Double Auctions with Dynamic Supply and Demand.
The 20th INFORMS Applied Probability Society Conference.
Taylor, P.
(2019). Some Thoughts About a Distributed Solution of the PageRank Equation.
Data Science Down Under 2019.
Fu, J., Nazarathy Y., Moka S.. B., & Taylor P.
(2019). Towards Q-learning the Whittle Index for Restless Bandits.
2019 Australian & New Zealand Control Conference (ANZCC). 249-254. doi: 10.1109/ANZCC47194.2019.8945748
Taylor, P.
(2019). Block arrivals in the Bitcoin blockchain.
16th Workshop on Algorithms and Models for the Web Graph (WAW 2019).
Bini, D., Hunter J., Latouche G., Meini B., & Taylor P.
(2018). Why is Kemeny's constant a constant?.
Australian Mathematical Society Conference, University of Adelaide Dec 4-7..
Bini, D., Hunter J., Latouche G., Meini B., & Taylor P.
(2018). Why is Kemeny's constant a constant?.
Colloquium, School of Mathematical Sciences, RMIT..
Taylor, P.
(2018). How does the Bitcoin blockchain work?.
CEBRE Seminar, School of Biosciences, University of Melbourne.
Taylor, P.
(2018). Modelling Block Arrivals in the Bitcoin Blockchain.
ICMS Conference on Stochastic Networks: Edinburgh, 25-29 June 2018..
Taylor, P., Fackrell M., & Costa A. M.
(2018). A Sequential Stochastic Mixed Integer Programming Model for Tactical Master Surgery Scheduling..
INFORMS 2018, The annual meeting of Institute for Operations Research and the Management Science, Phoenix, The United States. .
Bowden, R., Keeler H., Krzesinski A., & Taylor P.
(2018). Block arrivals in the Bitcoin blockchain.
Stochastic Models VI, Bedlewo, Poland..
Stanford, D., Taylor P., & Ziedins I.
(2018). Waiting Times in the Accumulating Priority Queue.
Conference of the Australian Society for Operations Research, Rydges Hotel, Parkville..
Taylor, P., Fackrell M., & Costa A. M.
(2018). A sequential stochastic mixed integer programming model for tactical master surgery scheduling..
ORAHS 2018, The 44th annual meeting of the EURO Working Group on Operational Research Applied to Health Services, Oslo, Norway..
Bowden, R., Keeler H., Krzesinski A., & Taylor P.
(2018). Block arrivals in the Bitcoin blockchain.
Colloquium, Department of MNanagement Science and Engineering, Stanford University.
Stanford, D., Taylor P., & Ziedins I.
(2018). Waiting Times in the Accumulating Priority Queue.
Australian Mathematical Society Conference, University of Adelaide Dec 4-7..
Mandjes, M., Taylor P., & Taylor P.
(2016). Markov-Modulated Erlang Loss Queues.
The 25th International Workshop on Matrices and Statistics (IWMS 2016).
Ivanovs, J., Latouche G., Taylor P., & Taylor P.
(2016). Scale Matrices for Matrix-Analytic Models.
Applied Probability Symposium.
Ivanovs, J., Latouche G., Taylor P., & Taylor P.
(2016). Lattice and Non-Lattice Markov Additive Models.
The Ninth International Conference on Matrix-Analytic Methods.
Taylor, P., & Tafakori L.
(2016). A model for cell proliferation in a developing organism.
ANZIAM (Australia and New Zealand Industrial and Applied Mathematics).
Taylor, P., & Tafakori L.
(2016). A model for cell proliferation in a developing organism.
World Congress in Probability and Statistics.
Journal Articles
Dandekar, R., Henderson S. G., Jansen H. M., McDonald J., Moka S., Nazarathy Y., et al.
(2021). Safe Blues: The case for virtual safe virus spread in the long-term fight against epidemics.
Patterns. 2(3), 100220. doi: 10.1016/j.patter.2021.100220
Bowden, R.., Keeler H. P., Krzesinski A. E., & Taylor P.
(2020). Modeling and analysis of block arrival times in the Bitcoin blockchain.
Stochastic Models. 36(4), 602-637. doi: 10.1080/15326349.2020.1786404
Mehra, S., McCaw J. M., Flegg M. B., Taylor P., & Flegg J. A.
(2020). An Activation-Clearance Model for Plasmodium vivax Malaria.
Bulletin of Mathematical Biology. 82(2), 32. doi: 10.1007/s11538-020-00706-1
Sonenberg, N., & Taylor P.
(2019). Networks of interacting stochastic fluid models with infinite and finite buffers.
Queueing Systems. 92(3-4), 293 - 322. doi: 10.1007/s11134-019-09619-w
Budd, J.K.., & Taylor P.
(2019). Bounds for the solution to the single-period inventory model with compound renewal process input: An application to setting credit card limits.
European Journal of Operational Research. 274(3), 1012 - 1018. doi: 10.1016/j.ejor.2018.11.022
Dendievel, S., Hautphenne S., Latouche G., & Taylor P.
(2019). The time-dependent expected reward and deviation matrix of a finite QBD process.
Linear Algebra and its Applications. 570, 61 - 92. doi: 10.1016/j.laa.2019.02.002
Bean, N. G., Latouche G., & Taylor P.
(2018). Physical Interpretations for Quasi-Birth-and-Death Process Algorithms.
Queueing Models and Service Management. 1(2), 59-78.
Kumar, A., Costa A. M., Fackrell M., & Taylor P.
(2018). A sequential stochastic mixed integer programming model for tactical masters surgery scheduling.
European Journal of Operational Research. 270(2), 734-746. doi: 10.1016/j.ejor.2018.04.007
Read, N., Duff T. J., & Taylor P.
(2018). A lightning-caused wildfire ignition forecasting model for operational use.
Agricultural and Forest Meteorology. 253-254, 233 - 246. doi: 10.1016/j.agrformet.2018.01.037
Loertscher, S., Muir E., & Taylor P.
(2017). A general noncentral hypergeometric distribution.
Communications in Statistics - Theory and Methods. 46, 4579-4598. doi: 10.1080/03610926.2015.1088033
Mandjes, M., Taylor P., & De Turck K..
(2017). The Markov-modulated Erlang loss system.
Performance Evaluation. 116, 53 - 69. doi: 10.1016/j.peva.2017.08.005
Li, N., Stanford D. A., Taylor P., & Ziedins I.
(2017). Nonlinear Accumulating Priority Queues with Equivalent Linear Proxies.
Operations Research. 65(6), 1712 - 1721. doi: 10.1287/opre.2017.1613
Hautphenne, S., Massaro M., & Taylor P.
(2017). How old is this bird? The age distribution under some phase sampling schemes.
Journal of Mathematical Biology. 75(6-7), 1319 - 1347. doi: 10.1007/s00285-017-1121-x
Saunders, K., Stephenson A. G., Taylor P., & Karoly D.
(2017). The spatial distribution of rainfall extremes and the influence of El Niño Southern Oscillation.
Weather and Climate Extremes. 18, 17 - 28. doi: 10.1016/j.wace.2017.10.001
Göbel, J., Keeler H., Krzesinski A., & Taylor P.
(2016). Bitcoin blockchain dynamics: The selfish-mine strategy in the presence of propagation delay.
Performance Evaluation. 104, 23-41. doi: 10.1016/j.peva.2016.07.001
Siekmann, I., Fackrell M., Crampin E. J., & Taylor P.
(2016). Modelling modal gating of ion channels with hierarchical Markov models.
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Science. 472(2192), 1-27. doi: 10.1098/rspa.2016.0122
Mandjes, M., & Taylor P.
(2016). The running maximum of a level-dependent quasi-birth-and-death process.
Probability in the Engineering and Informational Sciences. 30(02), 212-223. doi: 10.1017/S026996481500039X
Braunsteins, P., Hautphenne S., & Taylor P.
(2016). The roles of coupling and the deviation matrix in determining the value of capacity in M/M/1/C queues.
Queueing Systems. 83(1-2), 157-179. doi: 10.1007/s11134-016-9480-3
Maillardet, R. J., & Taylor P.
(2016). Queues with advanced reservations: An infinite-server proxy for the bookings diary.
Advances in Applied Probability. 48(01), 13-31. doi: 10.1017/apr.2015.4
Hautphenne, S., Kerner Y., Nazarathy Y., & Taylor P.
(2015). The intercept term of the asymptotic variance curve for some queueing output processes.
European Journal of Operational Research. 242(2), 455-464. doi: 10.1016/j.ejor.2014.10.051
Sonenberg, N., Au G., & Taylor P.
(2015). A queueing model for the capacity planning of a multi-phase human services process.
International Journal of Systems Science: Operations & Logistics. 2(3), 156-167. doi: 10.1080/23302674.2015.1015660
Keeler, H., & Taylor P.
(2014). Discussion on “On the Laplace Transform of the Aggregate Discounted Claims with Markovian Arrivals,” by Jiandong Ren, Volume 12(2).
North American Actuarial Journal. 19(1), 73-77. doi: 10.1080/10920277.2014.977453
Campbell, L. H., & Taylor P.
(2014). Renfrey Burnard Potts 1925–2005.
Historical Records of Australian Science. 25(2), 291. doi: 10.1071/HR14019
Stanford, D. A., Taylor P., & Ziedins I.
(2014). Waiting time distributions in the accumulating priority queue.
Queueing Systems. 77(3), 297-330. doi: 10.1007/s11134-013-9382-6
