Jacek Leskow
Rector of American University Kyiv, Prof. Dr.
- jacek.leskow[a]auk.edu.ua
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Professor at the EPAM School of Digital Technologies and Rector of American University Kyiv. An expert in cybersecurity, artificial intelligence, and data science, with extensive international experience in research, academic leadership, and technology-driven innovation. He previously served as Director of Poland’s National Cybersecurity Research Institute and led the development of the national AI strategy for Poland. His work focuses on advancing AI, data science, cybersecurity, and innovation in engineering education.
Jacek Leszkow is the Rector of American University Kyiv.
Before his appointment as Rector, Dr. Leszkow served as Dean of the EPAM School of Digital Technologies, where he led the development of academic programs and initiatives focused on academic excellence, career-oriented education, and strong partnerships with the IT industry.
Dr. Leszkow earned his PhD in Statistics and Mathematics from the Polish Academy of Sciences. He also served as Director of the National Cybersecurity Research Institute in Warsaw.
His professional expertise spans cybersecurity, artificial intelligence, and data science. Dr. Leszkow has served as a principal expert in research projects funded by NATO, the University of California, and the National Science Centre (NCN) of Poland, as well as initiatives in Mexico and Brazil. He led the working group of the Polish Ministry of Digital Affairs responsible for developing Poland’s National Artificial Intelligence Strategy and established the European Digital Innovation Hub in Kraków, focusing on the application of cybersecurity and artificial intelligence in the energy and transport sectors. In the field of data science, he founded and led the Data Science program at the Cracow University of Technology and managed the establishment of the National Institute of Data Science with the support of Poland’s National Centre for Research and Development (NCBR).
Dr. Leszkow has also developed learning environments for university data science programs using R, SPSS, and SAS in Poland, the United States, Mexico, Ukraine, and Brazil.
Throughout his career, he has gained extensive international leadership and management experience, working in the United States, Poland, Mexico, Brazil, France, Ukraine, and Kyrgyzstan.
As Rector of American University Kyiv, Dr. Leszkow is committed to expanding the University’s academic portfolio, strengthening its research activities, enhancing public outreach initiatives, and deepening collaboration with Arizona State University.
2025
69. Leśkow, J. (2025). Efficient Mutual Markets — A Global Perspective (monograph). Taylor and Francis, United Kingdom.
2024
68. Leśkow, J., Urbański, S., Rymkiewicz, B., & Stawiarski, B. (2024). Are global investment fund markets heading towards efficient markets? First Modern Finance Conference, Warsaw, September 2024. https://doi.org/10.2139/ssrn.4727036
67. Cioch, W., Duda, J., Leśkow, J., & Pawlik, P. (2024). CMAFI — Copula-based multifeature autocorrelation fault identification of rolling bearing. Mechanical Systems and Signal Processing, 211. https://doi.org/10.1016/j.ymssp.2024.111221
2023
66. Dehay, D., Leśkow, J., Napolitano, A., & Shevgunov, T. (2023). Cyclic detectors in the Fraction-of-Time probability framework. Inventions, 8(6), 152, pp. 1–23. https://doi.org/10.3390/inventions8060152
2022
65. Castro Morales, F. E., Politis, D. N., Leśkow, J., & Paez, M. S. (2022). Student's-t process with spatial deformation for spatio-temporal data. Statistical Methods and Applications, 31(5), 1099–1126. https://doi.org/10.1007/s10260-022-00623-8
2020
64. Urbański, S., Zarzecki, D., & Leśkow, J. (2020). Using the ICAPM to estimate the cost of capital: developed market and Polish market stock portfolios. In Education Excellence and Innovation Management: A 2025 Vision to Sustain Economic Development during Global Challenges (pp. 12858–12870). https://cris.pk.edu.pl/info/article/CUTfb8dc810bc6342e1a2dea8690c5aa154/
63. Gajecka, E., & Leśkow, J. (2020). Subsampling for heavy tailed, nonstationary and weakly dependent time series. In Cyclostationarity: Theory and Methods IV. Springer Verlag. https://doi.org/10.1007/978-3-030-22529-2
62. Urbański, S., & Leśkow, J. (2020). Using the ICAPM to estimate the capital cost of stock portfolios: empirical evidence on the Warsaw Stock Exchange. Statistics in Transition, 21(1), pp. 73–94.
2019
61. Skupień, M., & Leśkow, J. (2019). An application of functional data analysis to local damage detection. Statistics in Transition, 20(1), pp. 131–153.
2018
60. Dehay, D., Napolitano, A., & Leśkow, J. (2018). Time average estimation in the Fraction-of-Time probability framework. Signal Processing, 153, pp. 275–290.
2017
59. Rzecki, K., Pławiak, P., Niedźwiecki, M., Sosnicki, T., Ciesielski, M., & Leśkow, J. (2017). Person recognition based on touch screen gestures using computational intelligence methods. Information Sciences, 415–416, pp. 70–84.
58. de Andrade, B. S., Andrade, M. C., & Leśkow, J. (2017). Transformed GARMA model: properties and simulations. Communications in Statistics — Simulation and Computation, 46(9).
57. Andrade, B. S., Andrade, M. G., & Leśkow, J. (2017). Transformed GARMA model with the inverse Gaussian distribution. In Cyclostationarity: Theory and Methods III. Springer Verlag.
2016
56. Stawiarski, B., & Leśkow, J. (2016). Change-point problem in the Fraction-of-Time approach. In Cyclostationarity: Theory and Methods III. Springer Verlag.
55. Gajecka, E., & Leśkow, J. (2016). Resampling techniques for cyclostationary time series: long memory, weak dependence and heavy tails perspective. In Proceedings of the 60th World Statistics Congress of the International Statistical Institute. ISI Statistical Institute, The Netherlands.
2015
54. Andrade, B., Andrade, M., & Leśkow, J. (2015). Moving block quantile residual bootstrap in GARMA models: an application for the time series of dengue case count. In Proceedings of the 61st Annual Brazilian Region Meeting of the International Biometrics Society, Salvador, Bahia, Brazil.
53. Urbański, S., & Leśkow, J. (2015). Multifactor-efficiency of the Fama-French portfolios formed on the Warsaw Stock Exchange: bootstrap method application. Ekonomista, 2015(4).
52. Drake, C., Knapik, O., & Leśkow, J. (2015). Missing data analysis in cyclostationary models. Technical Transactions — Fundamental Sciences, 2-NP/2014. Cracow Technical University.
51. Dudek, A., Maiz, S., & Leśkow, J. (2015). Block bootstrap for the autocovariance coefficients of periodically correlated time series. In Akritas, S. N., Lahiri, S., & Politis, D. (Eds.), Topics in Nonparametric Statistics: Proceedings of the First Conference of the International Society for Nonparametric Statistics. Springer.
2014
50. Urbanski, S., & Leśkow, J. (2014). A new ICAPM approach to multifactor stock pricing using bootstrap. Folia Oeconomica Cracoviensia, LV. https://repozytorium.uafm.edu.pl/server/api/core/bitstreams/44965c7a-5fd6-4288-ad7d-b73da46e8c24/content
49. Garay, A., Castro, L. M., Lachos, V. H., & Leśkow, J. (2014). Censored linear regression models for irregularly observed longitudinal data using multivariate t-distribution. Statistical Methods in Medical Research. https://doi.org/10.1177/0962280214551191
48. Dudek, A., Paparoditis, E., Politis, D., & Leśkow, J. (2014). A generalized block bootstrap for seasonal time series. Journal of Time Series Analysis, 35, pp. 89–114.
47. Dehay, D., Dudek, A., & Leśkow, J. (2014). Subsampling for continuous-time almost periodically correlated processes. Journal of Statistical Planning and Inference, 150, pp. 142–158.
46. Drake, C., Knapik, O., & Leśkow, J. (2014). EM-based inference for cyclostationary time series with missing observations. In Chaari, F., Leśkow, J., Napolitano, A., & Sanchez-Ramirez, A. (Eds.), Cyclostationarity: Theory and Methods. Springer Verlag.
2013
45. Drake, C., Knapik, O., & Leśkow, J. (2013). Missing data analysis in cyclostationary models. Technical Journal of Politechnika Krakowska, Kraków.
44. Maiz, S., El Badaoui, M., Bonnardot, F., Dudek, A., & Leśkow, J. (2013). Deterministic/cyclostationary signal separation using bootstrap. In Proceedings of the 11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, University of Caen, France, July 2013.
43. Napolitano, A., Dehay, D., & Leśkow, J. (2013). Central limit theorem in the functional approach. IEEE Transactions on Signal Processing, 61(16), pp. 4025–4037.
42. Cioch, W., Knapik, O., & Leśkow, J. (2013). Finding a frequency signature for a cyclostationary signal with applications to wheel bearing diagnostics. Mechanical Systems and Signal Processing, 38, pp. 55–64.
2012
41. Leśkow, J. (2012). Cyclostationarity and resampling for vibroacoustic signals. Acta Physica Polonica A, 121, pp. 160–163.
40. Molenda, M., & Leśkow, J. (2012). Resampling methods for time series level crossings. Communications in Statistics — Theory and Methods, 42(23).
2011
39. Leśkow, J. (2011). Modeling stock market indexes with copula functions. eFinanse, 7(2).
38. Yavorskij, I., Isayev, I., Kravets, I., Gajecka, E., & Leśkow, J. (2011). Linear filtration methods for statistical analysis of periodically correlated random processes — Part II: harmonic series representation. Signal Processing, 91(11), pp. 2506–2519.
37. Yavorskij, I., Isayev, I., Kravets, I., Gajecka, E., & Leśkow, J. (2011). Linear filtration methods for statistical analysis of periodically correlated random processes — Part I: coherent and component method and their generalization. Signal Processing, 92, pp. 1559–1566.
2010
36. Dudek, A., & Leśkow, J. (2010). Bootstrap algorithm in periodic multiplicative intensity model. Communications in Statistics — Theory and Methods, 40(8), pp. 1468–1489.
2009
35. Synowiecki, R., & Leśkow, J. (2009). On bootstrapping periodic random arrays with increasing period. Metrika, 71(3), pp. 253–279.
2008
34. Lenart, L., Synowiecki, R., & Leśkow, J. (2008). Subsampling in estimation of autocovariance for PC time series. Journal of Time Series Analysis, 29(6), pp. 995–1018.
33. Dudek, A., Gócwin, M., & Leśkow, J. (2008). Simultaneous confidence bands for the integrated hazard function. Computational Statistics, 23(1), pp. 41–62.
2007
32. Lenart, L., Suseł, A., & Leśkow, J. (2007). Bootstrap and subsampling in financial risk management and demography. Monograph Tryptyk Sądecki (in Polish).
31. Napolitano, A., & Leśkow, J. (2007). Non-relatively measurable functions for secure communications signal design. Signal Processing, 87, pp. 2765–2780.
2006
30. Leśkow, J. (2006). Non-relatively measurable spread-sequences for secure transmission of direct-sequence spread-spectrum signals. In Proceedings of the XIV European Signal Processing Conference (EUSIPCO 2006), Florence, Italy.
29. Napolitano, A., & Leśkow, J. (2006). Foundations of the functional approach for signal analysis. Signal Processing, 86, pp. 3796–3825.
28. Lenart, L., & Leśkow, J. (2006). Applications of bootstrap and subsampling in financial risk assessment. Akademichnyj Oglyad, pp. 89–92, Ukraine.
2004
27. Napolitano, A., & Leśkow, J. (2004). Fraction-of-time approach in predicting Value-at-Risk. In Leśkow, J., Puchet, M., & Punzo, L. (Eds.), Lecture Notes in Mathematical Economics (pp. 183–200). Springer Verlag.
26. Wronka, C., & Leśkow, J. (2004). Bootstrap resampling tests for quantized time series. In Baier, D. & Wernecke, K.-D. (Eds.), Innovations in Classification, Data Science, and Information Systems: Proceedings of the 27th Annual GfKl Conference (pp. 267–274). Springer-Verlag.
2003
25. Matziol, A., & Leśkow, J. (2003). Inference for quantized spatial data using bootstrap. In Proceedings of IMPAN Conference on Probabilistic Methods in Atmospheric Sciences, Będlewo, December 2002.
2002
24. Napolitano, A., & Leśkow, J. (2002). Quantile prediction for time series in the fraction-of-time probability context. European Signal Processing Journal, 82, pp. 1727–1741.
2001
23. Iwanski, S., & Leśkow, J. (2001). Calculation of Value-at-Risk using the genetic algorithm. Rynek Terminowy, 2, pp. 130–136. (in Polish)
22. Leśkow, J. (2001). The impact of stationarity assessment on studies of volatility and Value-at-Risk. Mathematical and Computer Modelling, 34(9–11), pp. 1213–1222.
1999
21. Leśkow, J. (Ed.). (1999). Proceedings of the Conference 'Financial Markets and Regional Development'. Nowy Sącz, Poland.
20. Leśkow, J. (1999). Quantitative analysis of risk. In Proceedings of the Conference 'Financial Markets and Regional Development'. Nowy Sącz, Poland.
1997
19. Leśkow, J. (1997). Inference for nonstationary processes. In Proceedings of the XI Forum of Statistics, Culiacán, Mexico.
1996
18. Leśkow, J. (1996). Functional limit theory for a covariance estimator. Journal of Applied Probability, 33, pp. 1077–1092.
1995
17. Leśkow, J. (1995). Analysis of time series stationarity with applications. In Proceedings of the First Conference on Applied Statistics, Rider University, New Jersey, May 1995.
16. Dehay, D., & Leśkow, J. (1995). Testing stationarity for stock market data. Economics Letters, 50(2), pp. 205–212.
1994
15. Hurd, H. L., Cambanis, S., Houdré, C., & Leśkow, J. (1994). Laws of large numbers for periodically and almost periodically correlated processes. Stochastic Processes and Their Applications, 53, pp. 37–54.
14. Leśkow, J. (1994). Asymptotic normality of the spectral density estimators for almost periodically correlated stochastic processes. Stochastic Processes and Their Applications, 52, pp. 351–360.
1993
13. Leśkow, J. (1993). Sieve-based maximum likelihood estimator for almost periodic stochastic processes models. Probability and Mathematical Statistics, 14(1), pp. 11–24.
12. Leśkow, J. (1993). Asymptotic normality of the spectral density estimators for periodically correlated stochastic processes. In Puri, M. L. & Vilaplana, J. P. (Eds.), New Progress in Probability and Statistics (pp. 285–291). International Science Publishers.
1992
11. Hurd, H. L., & Leśkow, J. (1992). Strongly consistent and asymptotically normal estimation of the covariance for almost periodically correlated stochastic processes. Statistics and Decisions, 10, pp. 201–225.
10. Gorynska, W., & Leśkow, J. (1992). Morphometric diversification of red deer antlers from selected regions of Poland — symmetry, mean values. Folia Forestalia Polonica, 34, pp. 39–48. Series A — Forestry.
9. Weron, A., & Leśkow, J. (1992). Ergodic behaviour and estimation for periodically correlated processes. Statistics and Probability Letters, 15, pp. 299–304.
8. Hurd, H. L., & Leśkow, J. (1992). Estimation of the Fourier coefficient functions and their spectral densities for φ-mixing almost periodically correlated processes. Statistics and Probability Letters, 14, pp. 299–306.
1990
7. Gorynska, W., Kaczoruk, S., & Leśkow, J. (1990). An analysis of selected features of the European red deer antlers. Folia Forestalia Polonica, 32, pp. 5–18. Series A — Forestry.
1989
6. Rózański, R., & Leśkow, J. (1989). Maximum likelihood estimator of a drift function for a diffusion process. Statistics and Decisions, 7, pp. 243–262.
5. Leśkow, J. (1989). A note on kernel regularization of a histogram estimator in the multiplicative intensity model. Statistics and Probability Letters, 7, pp. 395–400.
4. Rózański, R., & Leśkow, J. (1989). Histogram maximum likelihood estimator in the multiplicative intensity model. Stochastic Processes and Their Applications, 31, pp. 151–189.
1988
3. Leśkow, J. (1988). Histogram maximum likelihood estimator of a periodic function in the multiplicative intensity model. Statistics and Decisions, 6, pp. 79–88.
1987
2. Leśkow, J. (1987). Estimation of a periodic function in the multiplicative intensity model. Probability and Mathematical Statistics, 8, pp. 103–110.
1984
1. Leśkow, J. (1984). On different versions of the law of iterated logarithm for R∞ and lp valued Wiener processes. Lecture Notes in Mathematics, 1080, pp. 152–161. Springer Verlag.