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- Radislav Vaisman
Dr Radislav Vaisman
Lecturer, Associate Investigator
The University of Queensland
I am a Lecturer in Data Science in the School of Mathematics and Physics in the University of Queensland. My research lies in the field of applied probability, stochastic simulation and machine learning. In particular, I am interested in the rare-events. These events are of great interest in many areas such as theoretical computer science, optimization and counting
Research Interests:
Advanced Monte Carlo Methods for rare event estimation
Combinatorial Optimization and Counting
Data Science
Design analysis and implementation of algorithms
Evolutionary computation
Machine Learning
Network reliability
Stochastic Simulation and Applied Probability
Qualifications:
PhD
Projects
Publications
Books
Kroese, D., Botev Z. I., Taimre T., & Vaisman R.
(2019). Data Science and Machine Learning: Mathematical and Statistical Methods.
Machine Learning & Pattern Recognition. 510.
Book Chapters
Gertsbakh, I. B., Shpungin Y., & Vaisman R.
(2018). Reliability of a Network with Heterogeneous Components.
(Lisnianski, A., Frenkel I., & Karagrigoriou A., Ed.).Recent Advances in Multi-state Systems Reliability. 3 - 18. doi: 10.1007/978-3-319-63423-4_1
Invited talks, refereed proceedings and other conference outputs
Shah, R., & Vaisman R.
(2016). New Sampling Plans for Estimating Residual Connectedness Reliability.
Annual International Conference on Operations Research and Statistics ( ORS 2016 ). doi: 10.5176/2251-1938_ORS16.18
Salomone, R., Vaisman R., & Kroese D.
(2016). Estimating the number of vertices in convex polytopes.
4th Annual International Conference on Operations Research and Statistics (ORS 2016). doi: 10.5176/2251-1938_ORS16.25
Journal Articles
Vaisman, R., & Kroese D.
(2018). On the analysis of independent sets via multilevel splitting.
Networks. 71(3), 281 - 301. doi: 10.1002/net.21805
Vaisman, R., & Kroese D.
(2017). Stochastic Enumeration Method for Counting Trees.
Methodology and Computing in Applied Probability. 19(1), 31 - 73. doi: 10.1007/s11009-015-9457-4
Vaisman, R., Roughan M., & Kroese D.
(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
Vaisman, R., Kroese D., & Gertsbakh I. 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
Vaisman, R., Kroese D., & Gertsbakh I. B.
(2016). Improved Sampling Plans for Combinatorial Invariants of Coherent Systems.
IEEE Transactions on Reliability. 65(1), 410 - 424. doi: 10.1109/TR.2015.2446471
Vaisman, R., Strichman O., & Gertsbakh I.
(2015). Model Counting of Monotone Conjunctive Normal Form Formulas with Spectra.
INFORMS Journal on Computing. 27(2), 406-415. doi: 10.1287/ijoc.2014.0633
Gertsbakh, I., Neuman E., & Vaisman R.
(2014). Monte Carlo for Estimating Exponential Convolution.
Communications in Statistics - Simulation and Computation. 44(10), 2696-2704. doi: 10.1080/03610918.2013.842591
Publicly available softwares
Kroese, D. P., Vaisman R., Taimre T., & Botev Z.
(2019). DSML-book.
Data Science and Machine Learning: Mathematical and Statistical Methods.