World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
45
Citations
21696
World Ranking
1410
National Ranking
34

Engineering and Technology

D-Index
45
Citations
21647
World Ranking
5321
National Ranking
275

Overview

Dirk P. Kroese is affiliated with the University of Queensland in Australia and has contributed extensively to the fields of computer science and mathematics. Their research spans several subfields, including artificial intelligence, statistics and probability, electrical and electronic engineering, management science and operations research, and numerical analysis.

The main topics of their work cover:

  • Machine Learning and Algorithms
  • Bayesian Modeling and Causal Inference
  • Bayesian Methods and Mixture Models
  • Reinforcement Learning in Robotics
  • Markov Chains and Monte Carlo Methods
  • Statistical Methods and Inference
  • Machine Learning and Data Classification

Kroese has authored multiple recent research papers in diverse and impactful venues. Selected publications include:

  • Chromosome arm aneuploidies shape tumour evolution and drug response, 2020, Nature Communications
  • Unbiased and consistent nested sampling via sequential Monte Carlo, 2025, Journal of the Royal Statistical Society Series B (Statistical Methodology)
  • Current Harmonics Generated by Multiple Adjustable-Speed Drives in Distribution Networks in the Frequency Range of 2-9 kHz, 2022, IEEE Transactions on Industry Applications
  • Detailed Estimation of Grid-Side Current and Its Oscillations Caused by Adjustable Speed Drive Systems, 2022, IEEE Transactions on Industrial Electronics
  • Model-based offline reinforcement learning for sustainable fishery management, 2023, Expert Systems

Frequently published venues include:

  • arXiv (Cornell University)
  • Nature Communications
  • Journal of the Royal Statistical Society Series B (Statistical Methodology)
  • IEEE Transactions on Industry Applications
  • IEEE Transactions on Industrial Electronics

The scientist's frequent coauthors include Joshua C. C. Chan, Hanna Kurniawati, Nan Ye, Marcus Hoerger, and Sarat Moka, reflecting collaborations across various research topics and projects.

In addition to articles, Dirk P. Kroese has contributed to academic publishing with a book titled Statistical Modeling and Computation, published by Springer International Publishing in 2025. This book adds to their scholarly output and engagement with the research community.

Best Publications

  • Simulation and the Monte Carlo Method

    R. Y. Rubinstein;D. P. Kroese

  • A Tutorial on the Cross-Entropy Method

    Pieter-Tjerk de Boer;Dirk P. Kroese;Shie Mannor;Reuven Y. Rubinstein

  • Kernel density estimation via diffusion

    Z. I. Botev;J. F. Grotowski;D. P. Kroese

  • The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation and Machine Learning

    Reuven Y. Rubinstein;Dirk P. Kroese

  • Handbook of Monte Carlo Methods

    Dirk P. Kroese;Thomas Taimre;Zdravko I. Botev

  • Simulation and the Monte Carlo Method (Wiley Series in Probability and Statistics)

    Reuven Y. Rubinstein;Dirk P. Kroese

  • Why the Monte Carlo method is so important today

    Dirk P. Kroese;Tim Brereton;Thomas Taimre;Zdravko I. Botev

  • The Cross Entropy Method: A Unified Approach To Combinatorial Optimization, Monte-carlo Simulation (Information Science and Statistics)

    Reuven Y. Rubinstein;Dirk P. Kroese

  • The Cross-Entropy Method for Continuous Multi-Extremal Optimization

    Dirk P. Kroese;Sergey Porotsky;Reuven Y. Rubinstein

  • The Cross‐Entropy Method

    Reuven Y. Rubinstein;Dirk P. Kroese

  • Application of the Cross-Entropy Method to the Buffer Allocation Problem in a Simulation-Based Environment

    G. Alon;Dirk P. Kroese;Tal Raviv;Reuven Y. Rubinstein

  • Improved algorithms for rare event simulation with heavy tails

    Søren Asmussen;Dirk P. Kroese

  • Monte Carlo methods

    Dirk P. Kroese;Reuven Y. Rubinstein

  • Convergence properties of the cross-entropy method for discrete optimization

    Andre Costa;Owen Dafydd Jones;Dirk Kroese

  • Efficient Monte Carlo simulation via the generalized splitting method

    Zdravko I. Botev;Dirk P. Kroese

  • The Cross-Entropy Method for Estimation

    Dirk P. Kroese;Reuven Y. Rubinstein;Peter W. Glynn

  • Chapter 3 – The Cross-Entropy Method for Optimization

    Zdravko I. Botev;Dirk P. Kroese;Reuven Y. Rubinstein;Pierre L’Ecuyer

  • The Cross-Entropy Method for Network Reliability Estimation

    Kin-Ping Hui;Nigel G. Bean;Miro Kraetzl;Dirk P. Kroese

  • Spatial Process Simulation

    Dirk P. Kroese;Zdravko I. Botev

  • An Efficient Algorithm for Rare-event Probability Estimation, Combinatorial Optimization, and Counting

    Zdravko I. Botev;Dirk P. Kroese

Frequent Co-Authors

Reuven Y. Rubinstein
Reuven Y. Rubinstein Technion – Israel Institute of Technology
Volker Schmidt
Volker Schmidt University of Ulm
Pierre L'Ecuyer
Pierre L'Ecuyer University of Montreal
Søren Asmussen
Søren Asmussen Aarhus University
Peter G. Taylor
Peter G. Taylor University of Melbourne
Shie Mannor
Shie Mannor Technion – Israel Institute of Technology
Peter W. Glynn
Peter W. Glynn Stanford University
Denis Andrienko
Denis Andrienko Max Planck Society
Ingo Manke
Ingo Manke Helmholtz-Zentrum Berlin für Materialien und Energie
René A. J. Janssen
René A. J. Janssen Eindhoven University of Technology

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