Zdravko Botev

Dr. Zdravko Botev is a Lecturer in Computational Statistics and Applied Probability at the School of Mathematics and Statistics, UNSW Sydney. He holds a PhD from the University of Queensland (2010) and has held postdoctoral fellowships at the Universities of Montreal and Cambridge. His research focuses on adaptive Monte Carlo methods, rare-event probability estimation, network reliability modeling, kernel density estimation, and model selection. He is the author of widely used MATLAB scripts for nonparametric density estimation and has contributed to influential texts like Data Science and Machine Learning: Mathematical and Statistical Methods.

Education:

• PhD in Statistics, University of Queensland, Australia, 2010

Research Interests:

Dr. Botev's work emphasizes computational statistics and rare-event simulation, with applications in network reliability and kernel density estimation. His methods address challenges in high-dimensional data analysis, Monte Carlo algorithms, and efficient statistical computation. Key areas include:
- Adaptive Monte Carlo methods for rare-event simulation
- Kernel density estimation techniques and boundary conditions
- Variance reduction strategies in statistical modeling

Professional Engagement:

• Member of the Australian Academy of Sciences Christopher Heyde Medal Awards Committee (2021–2023)
• Steering Committee member for the Monte Carlo Methods Conference
• Associate Editor for INFORMS Journal of Computing and Australian & New Zealand Journal of Statistics
• Chair of the organizing committee for the 12th International Conference on Monte Carlo Methods and Applications (2019)

Teaching:

Dr. Botev has taught courses such as Data Mining (MATH5836), Geotechnical Data Collection and Analysis (MINE8680), and Probability and Statistics (MATH2901/MATH2931). His teaching has received positive student evaluations for clarity and engagement.