Anna Kiriliouk

​I am an assistant professor in Statistics at the Faculty of Economics, Social Sciences
and Business Administration and the Department of Mathematics of the University
of Namur since September 2018. Before that, I was affiliated with the Erasmus University Rotterdam (EUR) as a fixed-term assistant professor and at the Université catholique de Louvain (UCLouvain) as a PhD student and postdoctoral researcher. 

My main research field is extreme value theory, with a focus on environmental applications, the development of statistical methodology for multivariate extremes, high-dimensional modelling, spatial extremes, and semi- and non-parametric inference. Recently, I've been particularly interested in topics related to the climate sciences, such as climate extreme event attribution and compound extremes.


Full cv: (pdf)
​Google scholar: (link)​

---

Agenda

• Invited talk at the workshop "Modern Statistical and Machine Learning Approaches for High-Dimensional Compound Spatial Extremes" (Granada, Spain, May 2023)
• Session Organizer at the 13th International Conference on Extreme Value Analysis (Milan, Italy, June 2023). 

Working papers

• Kiriliouk, A. and Zhou, C. (2022+). Estimating probabilities of multivariate failure sets based on pairwise tail dependence coefficients.​​

Accepted papers in peer-reviewed journals

• Kiriliouk, A. and Naveau, P. (2020). Climate extreme event attribution using multivariate peaks-over-thresholds modeling and counterfactual theory. Annals of Applied Statistics 14(3), 1342-1358.
• Kiriliouk, A. (2020). Hypothesis testing for tail dependence parameters on the boundary of the parameter space. ​​Econometrics and Statistics 16, 121-135.​
• ​Kiriliouk, A., Rootzén, H., Segers, J., and Wadsworth, J. (2019). Peaks over thresholds modelling with multivariate generalized Pareto distributions. Technometrics 61(1), 123-135.
• Kiriliouk, A., Segers, J. and Tafakori, L. (2018). An estimator of the stable tail dependence function based on the empirical beta copula. Extremes 21(4), 581-600.
• van Loenhout, J.A.F., Delbiso, T. Kiriliouk, A. Rodriguez-Llanes, J. Segers, J. and Guha-Sapir, D. (2018). Heat and emergency room admissions in the Netherlands. BMC Public Health 18(108), 1-9.
• Einmahl, J.H.J., Kiriliouk, A., and Segers, J. (2018). A continuous updating weighted least squares estimator of tail dependence in high dimensions. Extremes 21(2), 205-233. 
• Einmahl, J.H.J., Kiriliouk, A., Krajina, A., and Segers, J. (2016). An M-estimator of spatial tail dependence. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 78, 275-298. 
• Kiriliouk, A., Segers, J., and Warchol, M. (2016). Nonparametric estimation of extremal dependence. Book chapter in Extreme Value Modelling and Risk Analysis: Methods and Applications, edited by D. Dey and J. Yan. Chapman & Hall/CRC Press.
• Denuit, M., Kiriliouk, A., and Segers, J. (2015). Max-factor individual risk models with application to credit portfolios. Insurance: Mathematics and Economics, 62, 162-172.

Teaching  

• Statistics and probability for first-year students in Business engineering, Economics and Management.
• Statistics and probability for first-year students in Communication and Political Sciences.
• Linear algebra for second-year students in Business engineering, Economics and Management.
• Statistical inference and regression  for third-year students in Communication and Political Sciences.
• Regression for third-year students in Mathematics.
• Nonparametric statistics for master students in Business engineering.

PhD thesis

• Kiriliouk, A. (2016). Modelling extreme-value dependence in high dimensions using threshold exceedances.

R package

• tailDepFun.​ Provides functions implementing minimal distance estimation methods for parametric tail dependence models. A manual and a vignette are available. 

Contact

Email:        anna.kiriliouk at unamur.be
Address:    Faculté des sciences économiques, sociales et de gestion, room 433
                  Rempart de la vierge 8, B-5000 Namur, Belgique