Professor Dirk Kroese
Professor

Dirk Kroese

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+61 7 336 53287

Background

Dirk Kroese's research interests are in: Monte Carlo methods, rare-event simulation, the cross-entropy method, applied probability, and randomised optimisation.

Dirk Kroese is a professor of Mathematics and Statistics at the School of Mathematics and Physics of the University of Queensland. He has held teaching and research positions at The University of Texas at Austin, Princeton University, the University of Twente, the University of Melbourne, and the University of Adelaide. His research interests include Monte Carlo methods, adaptive importance sampling, randomized optimization, and rare-event simulation. He has over 120 peer-reviewed publications, including six monographs:

  • Rubinstein, R.Y., Kroese, D.P. (2004). The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation, and Machine Learning, Springer, New York.
  • Rubinstein, R. Y. , Kroese, D. P. (2007). Simulation and the Monte Carlo Method, 2nd edition, John Wiley & Sons.
  • Kroese, D.P., Taimre, T., and Botev, Z.I. (2011). Handbook of Monte Carlo Methods, Wiley Series in Probability and Statistics, John Wiley & Sons, New York.
  • Kroese, D.P. and Chan, J.C.C. (2014). Statistical Modeling and Computation, Springer, New York.
  • Rubinstein, R. Y. , Kroese, D. P. (2017). Simulation and the Monte Carlo Method, 3rd edition, John Wiley & Sons.
  • Kroese, D.P., Botev, Z.I., Taimre, T and Vaisman, R. (2019) Data Science and Machine Learning: Mathematical and Statistical Methods, Chapman & Hill/CRC.
  • Kroese, D.P. and Botev, Z.I. (2023). An Advanced Course in Probability and Stochastic Processes, Chapman & Hill/CRC.

Availability

Professor Dirk Kroese is:
Not available for supervision
Media expert

Fields of research

Applied mathematics Numerical and computational mathematics Statistics

Qualifications

  • Bachelor of Science, University of Twente
  • Masters (Coursework) of Science, University of Twente
  • Doctor of Philosophy, University of Twente

Research interests

  • The Cross-Entropy Method

    The CE methods involves an iterative procedure where each iteration can be broken down into two phases: (a) generate a randon data sample (trajectories, vectors, etc.) according to a specific mechanism; (b) update the parameters of the randdom mechanism based on this data in order to produce a better sample in the next iteration. I am one of the pioneers of the CE method. The simplicity and versatility of the method is explained in my book with R.Y. Rubinstein: The Cross Entropy Method: A Unified Approach to Combinatorial Optimisation. Monte-Carlo Simulation, and Machine Learning, Springer Verlag, 2004. The CE method has been applied to problems in systems reliability, buffer allocation, telecommunication systems, neural computation, control and navigation, DNA sequence alignment, scheduling and many more.

  • Monte Carlo Methods

    To better understand randomness, it is useful to perform random experiments on a computer. Such "Monte Carlo simulations" are nowadays an essential ingredient in many scientific investigations. Monte Carlo can be used in several different ways: (1) to mimic a random process so as to observe its behaviour, (2) to estimate numerical quantities (e.g., multidimensional integrals) via repeated simulation, and (3) to optimise a complicated (e.g., highly multi-modal) function.

Search Professor Dirk Kroese’s works on UQ eSpace

138 works between 1989 and 2024
All (138) Journal Article (81) Book Chapter (8) Conference Publication (37) Book (9) Other Outputs (2) Edited Outputs (1)

21 - 40 of 138 works

2018

Conference Publication

An on-line planner for POMDPs with large discrete action space: A quantile-based approach

Wang, Erli, Kurniawati, Hanna and Kroese, Dirk P. (2018). An on-line planner for POMDPs with large discrete action space: A quantile-based approach. 28th International Conference on Automated Planning and Scheduling ICAPS 2018, Delft, Netherlands, 24 - 29 June 2018. Menlo Park, CA United States: AAAI Press. doi: 10.1609/icaps.v28i1.13906

An on-line planner for POMDPs with large discrete action space: A quantile-based approach

2018

Journal Article

On the analysis of independent sets via multilevel splitting

Vaisman, Radislav and Kroese, Dirk P. (2018). On the analysis of independent sets via multilevel splitting. Networks, 71 (3), 281-301. doi: 10.1002/net.21805

On the analysis of independent sets via multilevel splitting

2018

Conference Publication

On a generalized splitting method for sampling from a conditional distribution

L'Ecuyer, Pierre, Botev, Zdravko I. and Kroese, Dirk P. (2018). On a generalized splitting method for sampling from a conditional distribution. 2018 Winter Simulation Conference, WSC 2018, Gothenburg, Sweden, 9-12 December 2018. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WSC.2018.8632422

On a generalized splitting method for sampling from a conditional distribution

2017

Journal Article

Splitting for Multi-objective Optimization

Duan, Qibin and Kroese, Dirk P. (2017). Splitting for Multi-objective Optimization. Methodology and Computing in Applied Probability, 20 (2), 517-533. doi: 10.1007/s11009-017-9572-5

Splitting for Multi-objective Optimization

2017

Journal Article

Without-replacement sampling for particle methods on finite state spaces

Shah, Rohan and Kroese, Dirk P. (2017). Without-replacement sampling for particle methods on finite state spaces. Statistics and Computing, 28 (3), 1-20. doi: 10.1007/s11222-017-9752-8

Without-replacement sampling for particle methods on finite state spaces

2017

Journal Article

The Multilevel Splitting algorithm for graph colouring with application to the Potts model

Vaisman, Radislav, Roughan, Matthew and Kroese, Dirk P. (2017). The Multilevel Splitting algorithm for graph colouring with application to the Potts model. Philosophical Magazine, 97 (19), 1646-1673. doi: 10.1080/14786435.2017.1312023

The Multilevel Splitting algorithm for graph colouring with application to the Potts model

2017

Journal Article

CEoptim: cross-entropy R package for optimization

Benham, Tim, Duan, Qibin, Kroese, Dirk P. and Liquet, Benoît (2017). CEoptim: cross-entropy R package for optimization. Journal of Statistical Software, 76 (1), 1-29. doi: 10.18637/jss.v076.i08

CEoptim: cross-entropy R package for optimization

2017

Conference Publication

CEMAB: a cross-entropy-based method for large-scale multi-armed bandits

Wang, Erli, Kurniawati, Hanna and Kroese, Dirk P. (2017). CEMAB: a cross-entropy-based method for large-scale multi-armed bandits. ACALCI 2017 Australasian Conference on Artificial Life and Computational Intelligence, Geelong, VIC, Australia, 31 January – 2 February 2017. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-51691-2_30

CEMAB: a cross-entropy-based method for large-scale multi-armed bandits

2017

Book

Simulation and the Monte Carlo method

Rubinstein, Reuven Y. and Kroese, Dirk P. (2017). Simulation and the Monte Carlo method. 3rd ed. Hoboken, NJ, United States: John Wiley and Sons. doi: 10.1002/9781118631980

Simulation and the Monte Carlo method

2017

Conference Publication

Efficient estimation of tail probabilities of the typical distance in preferential attachment models

Grant, Morgan R. and Kroese, Dirk P. (2017). Efficient estimation of tail probabilities of the typical distance in preferential attachment models. 2016 Winter Simulation Conference, WSC 2016, Arlington, VA, United States, 11 - 14 December 2016. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WSC.2016.7822101

Efficient estimation of tail probabilities of the typical distance in preferential attachment models

2016

Journal Article

Splitting sequential Monte Carlo for efficient unreliability estimation of highly reliable networks

Vaisman, Radislav, Kroese, Dirk P. and Gertsbakh, Ilya B. (2016). Splitting sequential Monte Carlo for efficient unreliability estimation of highly reliable networks. Structural Safety, 63, 1-10. doi: 10.1016/j.strusafe.2016.07.001

Splitting sequential Monte Carlo for efficient unreliability estimation of highly reliable networks

2016

Journal Article

Splitting for optimization

Duan, Qibin and Kroese, Dirk P. (2016). Splitting for optimization. Computers and Operations Research, 73, 119-131. doi: 10.1016/j.cor.2016.04.015

Splitting for optimization

2016

Journal Article

Improved sampling plans for combinatorial invariants of coherent systems

Vaisman, Radislav, Kroese, Dirk P. and Gertsbakh, Ilya B. (2016). Improved sampling plans for combinatorial invariants of coherent systems. IEEE Transactions on Reliability, 65 (1) 7161416, 410-424. doi: 10.1109/TR.2015.2446471

Improved sampling plans for combinatorial invariants of coherent systems

2016

Journal Article

A comparison of random walks in dependent random environments

Scheinhardt, Werner R. W. and Kroese, Dirk P. (2016). A comparison of random walks in dependent random environments. Advances in Applied Probability, 48 (1), 199-214. doi: 10.1017/apr.2015.13

A comparison of random walks in dependent random environments

2016

Journal Article

Fitting Laguerre tessellation approximations to tomographic image data

Spettl, A., Brereton, T., Duan, Q., Werz, T., Krill, C. E., Kroese, D. P. and Schmidt, V. (2016). Fitting Laguerre tessellation approximations to tomographic image data. Philosophical Magazine, 96 (2), 166-189. doi: 10.1080/14786435.2015.1125540

Fitting Laguerre tessellation approximations to tomographic image data

2016

Conference Publication

Estimating the number of vertices in convex polytopes

Salomone, Robert, Vaisman, Radislav and Kroese, Dirk (2016). Estimating the number of vertices in convex polytopes. 4th Annual International Conference on Operations Research and Statistics (ORS 2016), 5th Annual Conference on Computational Mathematics, Computational Geometry & Statistics (CMCGS 2016), Singapore, Singapore, 18 - 19 January 2016. Singapore, Singapore: Global Science and Technology Forum. doi: 10.5176/2251-1938_ORS16.25

Estimating the number of vertices in convex polytopes

2015

Journal Article

Stochastic Enumeration Method for Counting Trees

Vaisman, Radislav and Kroese, Dirk P (2015). Stochastic Enumeration Method for Counting Trees. Methodology and Computing in Applied Probability, 19 (1), 31-73. doi: 10.1007/s11009-015-9457-4

Stochastic Enumeration Method for Counting Trees

2015

Journal Article

Stochastic modeling and predictive simulations for the microstructure of organic semiconductor films processed with different spin coating velocities

Westhoff, D., Van Franeker, J. J., Brereton, T., Kroese, D. P., Janssen, R. A. J. and Schmidt, V. (2015). Stochastic modeling and predictive simulations for the microstructure of organic semiconductor films processed with different spin coating velocities. Modelling and Simulation in Materials Science and Engineering, 23 (4) 045003, 1-21. doi: 10.1088/0965-0393/23/4/045003

Stochastic modeling and predictive simulations for the microstructure of organic semiconductor films processed with different spin coating velocities

2015

Conference Publication

Rare event probability estimation for connectivity of large random graphs

Shah, Rohan, Hirsch, Christian, Kroese, Dirk P. and Schmidt, Volker (2015). Rare event probability estimation for connectivity of large random graphs. Winter Simulation Conference, WSC 2014, Savannah, GA, United States, 7-10 December 2014. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WSC.2014.7019916

Rare event probability estimation for connectivity of large random graphs

2015

Journal Article

Spatial process simulation

Kroese, Dirk P and Botev, Zdravko I (2015). Spatial process simulation. Lecture Notes in Mathematics, 2120, 369-404. doi: 10.1007/978-3-319-10064-7_12

Spatial process simulation

Past funding

  • 2021 - 2024
    Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries
    ARC Discovery Projects
    Open grant
  • 2018 - 2022
    High Quality and Robust Energy Conversion Systems for Distribution Networks
    ARC Linkage Projects
    Open grant
  • 2017 - 2019
    Large Scale Sequential Decision Making in an Uncertain World.
    United States Office of Naval Research
    Open grant
  • 2014 - 2021
    ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights (University of Melbourne lead institution)
    University of Melbourne
    Open grant
  • 2014 - 2016
    Advanced Monte Carlo Methods for Spatial Processes
    ARC Discovery Projects
    Open grant
  • 2012 - 2013
    Monte Carlo Methods for Spatial Stochastic Modeling
    Go8 Australia - Germany Joint Research Co-operation Scheme
    Open grant
  • 2011
    New-generation parallel-computing cluster for the mathematical and physical sciences
    UQ Major Equipment and Infrastructure
    Open grant
  • 2009 - 2013
    Improved Monte Carlo Methods for Estimation, Optimisation, and Counting
    ARC Discovery Projects
    Open grant
  • 2005 - 2007
    Cross-Entropy Methods in Complex Biological Systems
    ARC Discovery Projects
    Open grant
  • 2005 - 2007
    Rare Event Simulation with Heavy Tails
    ARC Discovery Projects
    Open grant
  • 2002
    Financial markets and network bandwidth
    University of Queensland Research Development Grants Scheme
    Open grant
  • 2000 - 2001
    Rare event simulation
    UQ New Staff Research Start-Up Fund
    Open grant

Availability

Professor Dirk Kroese is:
Not available for supervision

Supervision history

Current supervision

  • Doctor Philosophy

    L\'{e}vy Processes: Theory and Applications

    Associate Advisor

    Other advisors: Dr Kazutoshi Yamazaki

  • Master Philosophy

    Improved Exploration Methods for Deep Reinforcement Learning

    Associate Advisor

    Other advisors: Dr Nan Ye

  • Doctor Philosophy

    Reinforcement Learning for Partially Observable Environments

    Associate Advisor

    Other advisors: Dr Nan Ye

  • Doctor Philosophy

    Reinforcement Learning for Large and Complex Partially Observable Markov Decision Processes

    Associate Advisor

    Other advisors: Dr Nan Ye

  • Doctor Philosophy

    Statistical Models of Extreme Weather Events in a Changing Climate

    Associate Advisor

    Other advisors: Dr Meagan Carney

Completed supervision

Enquiries

Contact Professor Dirk Kroese directly for media enquiries about:

  • Monte Carlo simulation

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