Dr Slava Vaisman

Lecturer

Mathematics
Faculty of Science
r.vaisman@uq.edu.au
+61 7 336 53264

Overview

Radislav (Slava) Vaisman is a faculty member in the School of Mathematics and Physics at the University of Queensland. Radislav earned his Ph.D. in Information System Engineering from the Technion, Israel Institute of Technology in 2014. Radislav’s research interests lie at the intersection of applied probability, statistics, and computer science. Such a multidisciplinary combination allows him to handle both theoretical and real-life problems, in the fields of machine learning, optimization, safety, and system reliability research, and more. He has published in top-ranking journals such as Statistics and Computing, INFORMS, Journal on Computing, Structural Safety, and IEEE Transactions on Reliability. The Stochastic Enumeration algorithm, which was introduced and analyzed by Radislav Vaisman, had led to the efficient solution of several problems that were out of reach of state of the art methods. In addition, he is an author of 3 books with three of the most prestigious publishers in the field, Wiley, Springer, and CRC Press. Radislav serves on the editorial board of the Stochastic Models journal.

Research Interests

  • Data science
  • Statistics and Machine Learning
  • Rare Event Simulation and Modelling
  • System Reliability
  • Evolutionary Computation
  • Advanced Monte Carlo Methods and Randomized Algorithms
  • Stochastic Optimization and Counting
  • Graphical Models
  • Markov Decision Processes and Planning under uncertainty

Research Impacts

Radislav Vaisman’s research interests lie at the intersection of applied probability and computer science where he has made key contributions to the theory and the practical usage of Sequential Monte Carlo methods. Specifically, his work led to the publication of a book by John Wiley & Sons: Fast Sequential Monte Carlo Methods for Counting and Optimization, which covers the state-of-the-art of modern simulation techniques for counting and optimization. In addition, his contribution to the field of System Reliability resulted in the book: Ternary Networks: Reliability and Monte Carlo, by Springer. In 2019, Radislav coauthored the book: Data Science and Machine Learning: Mathematical and Statistical Methods, which was published by CRC Press. Dr. Vaisman has published in top-ranking journals such as Statistics and Computing, INFORMS, Journal on Computing, Structural Safety, Networks, and IEEE Transactions on Reliability.

Radislav Vaisman's research in the field of Sequential Monte Carlo led to the development of the Stochastic Enumeration method for estimating the size of backtrack trees. The proposed method tackles this very general but difficult problem in computational sciences. Dr. Vaisman also developed a rigorous analysis of the Stochastic Enumeration procedure and showed that it results in significant variance reduction as compared to available alternatives. In addition, he applied the multilevel splitting ideas to many practical applications, such as optimization, counting, and network studies. Dr. Vaisman has produced insightful work in the field of systems reliability, both in theory and practice. In particular, he has developed Sequential Monte Carlo methods for estimating failure probability in highly reliable structures and new sampling plans for estimating network reliability based on a network’s structural invariants. This contribution has been recognized by top scientific journals in this field, namely Structural Safety and IEEE Transactions on Reliability.

Qualifications

  • Doctor of Philosophy, Israel Institute of Technology
  • Master of Science, Open Uni Israel
  • Bachelor of Science, Technion, Israel Institute of Technology

Publications

View all Publications

Supervision

  • Doctor Philosophy

  • (2018) Doctor Philosophy

  • Master Philosophy

View all Supervision

Available Projects

  • Given a connected, undirected graph whose edges are labeled, the minimum labeling spanning tree (MLST) problem seeks a spanning tree whose edges have the smallest number of distinct labels (or colors). This problem has many real-life applications such as communication networks where each node can communicate via different types of channels. In this project, you will investigate various methods for solving the MLST problem. Reference: R.-S. Chang and L. Shing-Jiuan, “The minimum labeling spanning trees,” Information Processing Letters, vol. 63, no. 5, pp. 277–282, 1997, and X. Lai, Y. Zhou, J. He, and J. Zhang, “Performance Analysis of Evolutionary Algorithms for the Minimum Label Spanning Tree Problem,” IEEE Transactions on Evolutionary Computation, vol. 18, no. 6, pp. 860–872, Dec 2014.

  • The Dilworth’s problem and the corresponding chain decomposition of a partially ordered set (poset), is of critical importance in transportation/scheduling sciences. In this project, you will investigate advanced Monte Carlo methods for finding balanced decompositions. In particular, you will develop efficient algorithms for counting chain decompositions, and for constructing an optimal scheduling under uncertainty. The project has both theoretical and practical aspects. References: Helman I.Stern and Ilya B.Gertsbakh, Using deficit functions for aircraft fleet routing, Operations Research Perspectives, Volume 6, 2019.

View all Available Projects

Publications

Book

Book Chapter

  • Gertsbakh, Ilya B., Shpungin, Yoseph and Vaisman, Radislav (2018). Reliability of a network with heterogeneous components. Recent Advances in Multi-state Systems Reliability. (pp. 3-18) edited by .Cham, Switzerland: Springer. doi:10.1007/978-3-319-63423-4_1

Journal Article

Conference Publication

  • Moreno, Gabriel A., Strichman, Ofer, Chaki, Sagar and Vaisman, Radislav (2017). Decision-making with cross-entropy for self-adaptation. 12th IEEE/ACM International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2017, Buenos Aires, Argentina, 22 - 23 May 2017. Piscataway, NJ, United States :Institute of Electrical and Electronics Engineers. doi: 10.1109/SEAMS.2017.7

  • Gertsbakh, Ilya B. , Shpungin, Yoseph and Vaisman, Radislav (2016). D-spectra for networks with binary and ternary components. Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO’16), Beer Sheva, Israel, 15 -18 Febuary 2016. Piscataway, NJ, United States :Institute of Electrical and Electronics Engineers. doi: 10.1109/SMRLO.2016.44

  • 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

  • Shah, Rohan and Vaisman, Radislav (2016). New sampling plans for estimating residual connectedness reliability. 4th Annual International Conference on Operations Research and Statistics (ORS 2016), City of Singapore, Singapore, 18-19 January 2016. Singapore :Global Science and Technology Forum. doi: 10.5176/2251-1938_ORS16.18

  • Botev, Zdravko I., Vaisman, Slava, Rubinstein, Reuven Y. and L’Ecuyer, Pierre (2014). Reliability of stochastic flow networks with continuous link capacities. 2014 Winter Simulation Confernce, Savannah, GA, USA, 7-10 December 2014. Piscataway, NJ United States :Institute of Electrical and Electronics Engineers. doi: 10.1109/WSC.2014.7019919

Grants (Administered at UQ)

PhD and MPhil Supervision

Current Supervision

  • Doctor Philosophy — Joint Principal Advisor

    Other advisors:

  • Master Philosophy — Associate Advisor

    Other advisors:

Completed Supervision

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.

  • Given a connected, undirected graph whose edges are labeled, the minimum labeling spanning tree (MLST) problem seeks a spanning tree whose edges have the smallest number of distinct labels (or colors). This problem has many real-life applications such as communication networks where each node can communicate via different types of channels. In this project, you will investigate various methods for solving the MLST problem. Reference: R.-S. Chang and L. Shing-Jiuan, “The minimum labeling spanning trees,” Information Processing Letters, vol. 63, no. 5, pp. 277–282, 1997, and X. Lai, Y. Zhou, J. He, and J. Zhang, “Performance Analysis of Evolutionary Algorithms for the Minimum Label Spanning Tree Problem,” IEEE Transactions on Evolutionary Computation, vol. 18, no. 6, pp. 860–872, Dec 2014.

  • The Dilworth’s problem and the corresponding chain decomposition of a partially ordered set (poset), is of critical importance in transportation/scheduling sciences. In this project, you will investigate advanced Monte Carlo methods for finding balanced decompositions. In particular, you will develop efficient algorithms for counting chain decompositions, and for constructing an optimal scheduling under uncertainty. The project has both theoretical and practical aspects. References: Helman I.Stern and Ilya B.Gertsbakh, Using deficit functions for aircraft fleet routing, Operations Research Perspectives, Volume 6, 2019.