User:CEmethod/sandbox
Dirk P. Kroese | |
|---|---|
| Born | 1963 (age 61–62) |
| Scientific career | |
| Fields | Mathematics AND Statistics |
| Institutions | The University of Queensland |
| Thesis | Stochastic Models in Reliability (1990) |
Dirk Pieter Kroese (born 1963) is a Dutch-Australian mathematician and statistician, and Professor at the University of Queensland. He is known for several contributions to Monte Carlo methods and ***. He is, with Reuven Rubinstein, the pioneer of the Cross-entropy_method.
Biography
Born in Wapenveld (municipality of Heerde), Dirk Kroese received his Ph.D. (cum laude) in Applied Mathematics from the University of Twente in 1990 on the dissertation entitled "Stochastic Models in Reliability. His PhD advisors were Joseph H. A. de Smit and Wilbert C. M. Kallenberg [1]. Part of his PhD research, (during 1989 and 1989), was carried out at Princeton University under the guidance of Erhan Çinlar
Dirk Kroese has held teaching and research positions at .. Full professor [2] since ...
Work
Dirk Kroese's work spans ... of applied probability, mathematical statistics. Dirk Kroese's research interests are in: Monte Carlo methods, rare-event simulation, the cross-entropy method, applied probability, and randomised optimisation.
ACEMS[3]
homepage[4]
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 [5], including six monographs:
Publications
Books:
- 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, CRC Press.
Selected Articles:
- de Boer, Kroese, D.P., Mannor, S. and Rubinstein, R.Y. (2005) A tutorial on the cross-entropy method. Annals of Operations Research 134 (1), 19-67.
- Botev, Z.I., Grotowski J.F., Kroese, D.P. (2010). Kernel density estimation via diffusion. The Annals of Statistics 38 (5), 2916-2957.
- Kroese, D.P., Brereton. T., Taimre, T. and Botev Z.I. (2014). Why the Monte Carlo method is so important today. Wiley Interdisciplinary Reviews: Computational Statistics 6 (6), 386-392.
- Kroese, D.P., Porotsky S., Rubinstein, R.Y. (2006) The cross-entropy method for continuous multi-extremal optimization. Methodology and Computing in Applied Probability 8 (3), 383-407.
- Asmussen, S. and Kroese, D.P. Improved algorithms for rare event simulation with heavy tails (2006). Advances in Applied Probability 38 (2), 545-558.
- Botev, Z.I. and Kroese, D.P. Efficient Monte Carlo simulation via the generalized splitting method (2012). Statistics and Computing 22 (1), 1-16.