Personal page
Jacek Leśkow Ph.D, short bio-note
Born: Nov 1, 1959. Polish and US citizen. Married, two adult children.
e-mail: jacek.leskow200@gmail.com
tel: +48.535.373.606,
Main professional engagements.
Since February 2024 Rector of American University in Kyiv
Since July 2023 Dean of the EPAM School of Digital Technologies, American University, Kyiv
2018-2020 NASK National Cybersecurity Research Institute, Warsaw, Director.
from 2012 Cracow University of Technology, Cracow, Professor.
1997 – 2012 WSB-NLU Polish-American Business School, Nowy Sącz.
Deputy Rector for Research.
from 1989 University of California, USA ( until 1997 – full time, later –
part-time), Professor.
Professional expertise (selected)
Cybersecurity and Artificial Intelligence.
· Has developed new prediction algorithms for time series and signals. Applications in mining, machine industry, finance. Principal investigator of research projects from NATO, University of California, National Center for Science (NCN) in Poland, Mexico and Brazil. Has authored 5 research books (Springer), 65 publications in international journals, leadership of the international research group (since 2000).
· Has headed the main Polish cybersecurity research institute NASK in Warsaw, Poland. Has headed the Ministry of Digitalization group developing the strategy of AI for Poland. Has headed applications of AI tools into the nationwide public administration platform EZD. Has headed the group building the nationwide OSE telecommunication fiberoptics network (2018-2020).
· Has created the European Digital Innovation Hub in Cracow focused on applications of cybersecurity and AI in energy and transportation sector. Established cooperation networks with similar centers across Central Europe.
Data Science.
· Created and chaired the program in Data Science at Cracow University of Technology. Established strong interactions with IBM and other business units for students and faculty.
· Leadership of the project of creating the National Institute of Data Science sponsored by National Center of Research and Development (NCBR) in Poland.
· Created learning environments for University Data Science programs using R, SPSS, SAS in Poland, US, Mexico, Ukraine and Brazil.
· Consulted financial institutions in predictive modelling using time series.
International Experience.
· Projects (instructions, problem solving, consulting) in risk management, operations
management, financial risk management and cross cultural management.
· Member of the Advisory Council to the US Ambassador in Poland.
· Has worked in the US, Poland, Mexico, Brazil, France, Ukraine and Kyrgyzstan.
· Speaks fluently: English, French, Spanish, Russian and Portuguese (Brazil).
Management experience (selected)
· Rector, American University Kyiv.
· Director, NASK Institute for Cybersecurity, Poland.
· Director, Statistical Consulting Lab, University of California, USA.
· Principal investigator, NATO international research grant on
securing the telecommunication signals.
· Deputy Rector for Research, Polish-American Business School,
Nowy Sącz, Poland.
· Principal investigator, Polish Research Agency grant on statistical
signal processing.
· Member of the Małopolska regional committee
on distribution of EU infrastructural funds (MRPO)
Publications
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.