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

139 works between 1989 and 2024
All (139) Journal Article (82) Book Chapter (8) Conference Publication (37) Book (9) Other Outputs (2) Edited Outputs (1)

1 - 20 of 139 works

2024

Journal Article

Adaptive discretization using Voronoi trees for continuous pOMDPs

Hoerger, Marcus, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2024). Adaptive discretization using Voronoi trees for continuous pOMDPs. The International Journal of Robotics Research, 43 (9), 1283-1298. doi: 10.1177/02783649231188984

Adaptive discretization using Voronoi trees for continuous pOMDPs

2024

Journal Article

A Surprisingly Simple Continuous-Action POMDP Solver: Lazy Cross-Entropy Search Over Policy Trees

Hoerger, Marcus, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2024). A Surprisingly Simple Continuous-Action POMDP Solver: Lazy Cross-Entropy Search Over Policy Trees. Proceedings of the AAAI Conference on Artificial Intelligence, 38 (18), 20134-20142. doi: 10.1609/aaai.v38i18.29992

A Surprisingly Simple Continuous-Action POMDP Solver: Lazy Cross-Entropy Search Over Policy Trees

2024

Conference Publication

A surprisingly simple continuous-action POMDP solver: lazy cross-entropy search over policy trees

Hoerger, Marcus, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2024). A surprisingly simple continuous-action POMDP solver: lazy cross-entropy search over policy trees. 38th AAAI Conference on Artificial Intelligence (AAAI) / 36th Conference on Innovative Applications of Artificial Intelligence / 14th Symposium on Educational Advances in Artificial Intelligence, Vancouver, Canada, 20-27 February 2024. Palo Alto, CA, United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v38i18.29992

A surprisingly simple continuous-action POMDP solver: lazy cross-entropy search over policy trees

2023

Book

An advanced course in probability and stochastic processes

Kroese, Dirk P. and Botev, Zdravko I. (2023). An advanced course in probability and stochastic processes. New York, NY United States: Chapman and Hall. doi: 10.1201/9781003315018

An advanced course in probability and stochastic processes

2023

Journal Article

Detailed estimation of grid-side current and its oscillations caused by adjustable speed drive systems

Moradi, Arash, Farajizadeh, Farzad, Zare, Firuz, Kumar, Dinesh, Rathnayake, Hansika, Sharma, Rahul and Kroese, Dirk (2023). Detailed estimation of grid-side current and its oscillations caused by adjustable speed drive systems. IEEE Transactions on Industrial Electronics, PP (99), 1-10. doi: 10.1109/tie.2022.3206695

Detailed estimation of grid-side current and its oscillations caused by adjustable speed drive systems

2023

Journal Article

Model‐based offline reinforcement learning for sustainable fishery management

Ju, Jun, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2023). Model‐based offline reinforcement learning for sustainable fishery management. Expert Systems, 42 (1) e13324. doi: 10.1111/exsy.13324

Model‐based offline reinforcement learning for sustainable fishery management

2022

Conference Publication

Adaptive Discretization Using Voronoi Trees for Continuous-Action POMDPs

Hoerger, Marcus, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2022). Adaptive Discretization Using Voronoi Trees for Continuous-Action POMDPs. Fifteenth Workshop on the Algorithmic Foundations of Robotics WAFR 2022, College Park, MD United States, 22-24 June 2022. Cham, Switzerland: Springer. doi: 10.1007/978-3-031-21090-7_11

Adaptive Discretization Using Voronoi Trees for Continuous-Action POMDPs

2022

Journal Article

Current harmonics generated by multiple adjustable speed drives in distribution networks in the frequency range of 2-9 kHz

Moradi, Arash, Zare, Firuz, Kumar, Dinesh, Yaghoobi, Jalil, Sharma, Rahul and Kroese, Dirk (2022). Current harmonics generated by multiple adjustable speed drives in distribution networks in the frequency range of 2-9 kHz. IEEE Transactions on Industry Applications, 58 (4), 1-1. doi: 10.1109/tia.2022.3172024

Current harmonics generated by multiple adjustable speed drives in distribution networks in the frequency range of 2-9 kHz

2022

Book Chapter

Rare-event simulation via neural networks

Gibson, Lachlan J. and Kroese, Dirk P. (2022). Rare-event simulation via neural networks. Advances in Modeling and Simulation. (pp. 151-168) edited by Botev, Zdravko, Lemieux, Christiane, Keller, Alexander and Tuffin, Bruno. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-031-10193-9_8

Rare-event simulation via neural networks

2022

Journal Article

Simulating rare events in queues via neural networks

Kroese, Dirk P. and Gibson, Lachlan J. (2022). Simulating rare events in queues via neural networks. Queueing Systems, 100 (3-4), 537-539. doi: 10.1007/s11134-022-09751-0

Simulating rare events in queues via neural networks

2021

Conference Publication

Shadow Manifold Hamiltonian Monte Carlo

van der Heide, Chris, Hodgkinson, Liam, Roosta, Fred and Kroese, Dirk (2021). Shadow Manifold Hamiltonian Monte Carlo. International Conference on Artificial Intelligence and Statistics, Online, 27-30- July 2021. Tempe, AZ, United States: ML Research Press.

Shadow Manifold Hamiltonian Monte Carlo

2021

Conference Publication

Current harmonics generated by multi-power converters in distribution networks in the frequency range of 2-9 kHz

Moradi, Arash, Yaghoobi, Jalil, Zare, Firuz, Kumar, Dinesh, Sharma, Rahul and Kroese, Dirk (2021). Current harmonics generated by multi-power converters in distribution networks in the frequency range of 2-9 kHz. IEEE 19th International Power Electronics and Motion Control Conference (PEMC), Gliwice, Poland, 25-29 April 2021. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/PEMC48073.2021.9432621

Current harmonics generated by multi-power converters in distribution networks in the frequency range of 2-9 kHz

2021

Journal Article

Rare events in random geometric graphs

Hirsch, Christian, Moka, Sarat B., Taimre, Thomas and Kroese, Dirk P. (2021). Rare events in random geometric graphs. Methodology and Computing in Applied Probability, 24 (3), 1367-1383. doi: 10.1007/s11009-021-09857-7

Rare events in random geometric graphs

2021

Conference Publication

MOOR: Model-based offline reinforcement learning for sustainable fishery management

Ju, Jun, Kurniawati, Hanna, Kroese, Dirk and Ye, Nan (2021). MOOR: Model-based offline reinforcement learning for sustainable fishery management. 24th International Congress on Modelling and Simulation, Sydney, NSW, Australia, 5 - 10 December 2021. Sydney, NSW, Australia: International Congress on Modelling and Simulation. doi: 10.36334/modsim.2021.M2.ju

MOOR: Model-based offline reinforcement learning for sustainable fishery management

2020

Journal Article

Perfect sampling for Gibbs point processes using partial rejection sampling

Moka, Sarat B. and Kroese, Dirk P. (2020). Perfect sampling for Gibbs point processes using partial rejection sampling. Bernoulli, 26 (3), 2082-2104. doi: 10.3150/19-BEJ1184

Perfect sampling for Gibbs point processes using partial rejection sampling

2020

Journal Article

Chromosome arm aneuploidies shape tumour evolution and drug response

Shukla, Ankit, Nguyen, Thu H. M., Moka, Sarat B., Ellis, Jonathan J., Grady, John P., Oey, Harald, Cristino, Alexandre S., Khanna, Kum Kum, Kroese, Dirk P., Krause, Lutz, Dray, Eloise, Fink, J. Lynn and Duijf, Pascal H. G. (2020). Chromosome arm aneuploidies shape tumour evolution and drug response. Nature Communications, 11 (1) 449, 449. doi: 10.1038/s41467-020-14286-0

Chromosome arm aneuploidies shape tumour evolution and drug response

2019

Conference Publication

Exact posterior simulation from the linear lasso regression

Botev, Zdravko, Chen, Yi-Lung, L'Ecuyer, Pierre, MacNamara, Shev and Kroese, Dirk P. (2019). Exact posterior simulation from the linear lasso regression. 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.2018.8632237

Exact posterior simulation from the linear lasso regression

2019

Conference Publication

Inventory control with partially observable states

Wang, Erli, Kurniawati, Hanna and Kroese, Dirk P. (2019). Inventory control with partially observable states. 23rd International Congress on Modelling and Simulation - Supporting Evidence-Based Decision Making: The Role of Modelling and Simulation, MODSIM 2019, Canberra, ACT, Australia, 1 - 6 December 2019. Modelling and Simulation Society of Australia and New Zealand Inc. (MSSANZ). doi: 10.36334/modsim.2019.B1.wang

Inventory control with partially observable states

2019

Conference Publication

Unbiased estimation of the reciprocal mean for non-negative random variables

Moka, Sarat Babu, Kroese, Dirk P. and Juneja, Sandeep (2019). Unbiased estimation of the reciprocal mean for non-negative random variables. 2019 Winter Simulation Conference (WSC), National Harbor, MD, United States, 8-11 December 2019. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/wsc40007.2019.9004815

Unbiased estimation of the reciprocal mean for non-negative random variables

2019

Book Chapter

Monte Carlo Methods

Taimre, Thomas , Kroese, Dirk P. and Botev, Zdravko I. (2019). Monte Carlo Methods. Wiley StatsRef: Statistics Reference Online. (pp. 1-10) edited by N. Balakrishnan, T. Colton, B. Everitt, W. Piegorsch, F. Ruggeri and J. L. Teugels. Hoboken, NJ United States: Wiley-Blackwell. doi: 10.1002/9781118445112.stat03619.pub2

Monte Carlo Methods

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

  • Master Philosophy

    Improved Exploration Methods for Deep Reinforcement Learning

    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

  • Doctor Philosophy

    Reinforcement Learning for Partially Observable Environments

    Associate Advisor

    Other advisors: Dr Nan Ye

  • Doctor Philosophy

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

    Associate Advisor

    Other advisors: Dr Kazutoshi Yamazaki

Completed supervision

Enquiries

Contact Professor Dirk Kroese directly for media enquiries about:

  • Monte Carlo simulation

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