Research in the field of Data Analytics and Artificial Intelligence:

At the University of Warmia and Mazury in Olsztyn, the Faculty of Mathematics and Computer Science is a leading centre of innovation in the field of data analytics and artificial intelligence. Our specialist research group, which includes recognised experts, dedicates its work to developing advanced technologies and methods that transform the way we analyse and interpret data.

Our focus is on pioneering the use of artificial intelligence to analyse data, enabling us to discover new patterns, predict trends and make decisions based on robust data. Our research and projects cover a wide range of applications, from modelling ecological interaction networks and sensor-based detection of agricultural diseases, to elastodynamics of structured media and securing digital communications. We apply these skills to push the limits of decision-making complexity in information sciences.

We have in-depth knowledge and skills in: Advanced data analytics, using artificial intelligence to understand medical, economic and other data. Building and implementing machine learning models for employee loyalty analysis, classification and forecasting. Using statistical techniques and multivariate data analysis, including PCA, SVM, granular computing methods and various clustering methods, to extract knowledge from large data sets. Applications of neural networks, including rough fuzzy networks, hypercomplex neural networks in decision-making and control processes.

UWM's Department of Mathematics and Computer Science is a place where the theory of data analysis and artificial intelligence is transformed into practical solutions, driving innovation and development in various fields.

Our staff are involved in a number of research topics in the area of computer science, including approximation algorithms and their relationship to integral system theory, applied computer science, mobile robot navigation, image reconstruction, sequence alignment, logic under uncertain conditions.

List of selected publications (out of several hundred)

[55] Lech T. Polkowski: Logic: Reference Book for Computer Scientists - The 2nd Revised, Modified, and Enlarged Edition of "Logics for Computer and Data Sciences, and Artificial Intelligence". Intelligent Systems Reference Library 245, Springer 2023, ISBN 978-3-031-42033-7, pp. 1-450

[54] S. Dutta, Ślęzak D., Nature of Decision Valuations in Elimination of Redundant Attributes, International Journal of Approximate Reasoning (109091), Volume 165, 2024 (https://doi.org/10.1016/j.ijar.2023.109091)

[53] S. Dutta, A. Skowron, L. Sosnowski, Medical Decision Support in the Light in Interactive Granular Computing: Lessons from the OvuFriend Project, International Journal of Approximate Reasoning (109103), Volume 165, 2024 (https://doi.org/10.1016/j.ijar.2023.109103)

[52] Kruk, M. 2023. Prediction of environmental factors responsible for chlorophyll a-induced hypereutrophy using explainable machine learning. Ecological Informatics 75: 102005. https://doi.org/10.1016/j.ecoinf.2023.102005, 4.498 IF

[51] Pakulnicka, J., Kruk M. 2023. Regional differences in water beetle communities networks settling in dystrophic lakes in northern Poland. Scientific Reports 13:12699. tps://doi.org/10.1038/s41598-023-39689-z. 4.996 IF

[50] Goździejewska A.M., Kruk, M. 2023. The response of zooplankton network indicators to winter water warming using shallow artifcial reservoirs as model case study. Scientific Reports 13:18002. | https://doi.org/10.1038/s41598-023-45430-7. 4.996 IF

[49] Navigational Strategies for Mobile Robots Using Rough Mereological Potential Fields and Weighted Distance to Goal
Szpakowska Aleksandra, Artiemjew Piotr Lech, Cybowski Wojciech, W: Rough Sets : International Joint Conference, IJCRS 2023, Kraków, Poland, October 5-8, 2023, Proceedings / Campagner Andrea [i in.] (red.), Lecture Notes in Computer Science, 2023, nr 14481, Cham, Springer, s.549-564, ISBN 978-3-031-50959-9

[48] Yakovyna, V., Uhrynovskyi, B., Shakhovska, N.: A Comprehensive Model of Android Software Aging and Rejuvenation Considering Battery Saving. Electronics 12(7), 1600 (2023). https://doi.org/10.3390/electronics12071600

[47] A. Doliwa, A. Siemaszko, Integrability and geometry of the Wynn
recurrence, Numer. Algorithms 92 (2023) 571-596, doi: 10.1007/s11075-
022-01344-5

[46] A. Doliwa, A. Siemaszko, Hermite-Padé approximation and
integrability, J. Approx. Theory 292 (2023) 105910 (23 pp.)
doi: 10.1016/j.jat.2023.105910

[45] Aleksander Denisiuk: Weighted Hamming Metric and KNN Classification of
Nominal-Continuous Data, Computational Science – ICCS 2023. Lecture Notes in
Computer Science, Vol. 14074, Springer, Cham (2023)

[44] M. Kuprowski, P. Drozda (2023). Feature Selection for Airbone LiDAR Point Cloud Classification. Remote Sensing, 15(3), 561. (100 pkt)

[43] P. Drozda, B. Nowak, A. Talun, L. Bukowski, (2023, September). Evaluating Web Crawlers with Machine Learning Algorithms for Accurate Location Extraction from Job Offers. In International Conference on Computational Collective Intelligence (pp. 300-312). Cham: Springer Nature Switzerland. (70 pkt)

[42] M. Osowski, K. Lorenc, P. Drozda, R. Scherer, K. Szałapak, K. Komar-Komarowski, A. Sobecki, (2023, September). Previous Opinions is All You Need—Legal Information Retrieval System. In International Conference on Computational Collective Intelligence (pp. 57-67). Cham: Springer Nature Switzerland. (70 pkt)

[41] Krzywicki, T.; Brona, P.; Zbrzezny, A.M.; Grzybowski, A.E. (2023) A Global Review of Publicly Available Datasets Containing Fundus Images: Characteristics, Barriers to Access, Usability, and Generalizability. J. Clin. Med.2023, 12, 3587. https://doi.org/10.3390/jcm12103587 (140 pt, IF 4.964)

[40] P. Jastrzębski, A.Lecko, An Evolutionary Approach to the Coefficient Problems in the Class of Starlike Functions, Electronic Transactions on Numerical Analysis, vol. 58, 2023, pp. 568–58.

[39] Artiemjew, P. and Tadeja, S. (2022). Using ConvNet for Classification Task in Parallel Coordinates Visualization of Topologically Arranged Attribute Values. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-547-0, pages 167-171. DOI: 10.5220/0010793700003116

[38] Weiss, A., Młyński, M., & Artiemjew, P. (2022). About Classifiers Quality Assessment: Balanced Accuracy Curve (BAC) as an alternative for ROC and PR Curve. In M. Ganzha, L. Maciaszek, M. Paprzycki, & D. Ślęzak (Eds.), Proceedings of the 17th Conference on Computer Science and Intelligence Systems (Vol. 30, pp. 149-156). IEEE. https://doi.org/10.15439/2022F262

[37] Cybulski, R., Artiemjew, P. "Accelerating concept-dependent granulation technique using data decomposition," 2022 IEEE International Conference on Big Data (Big Data), pp. 6177 -- 6183, IEEE Catalog Number: CFP22BGD-ART, ISBN: 978-1-6654-8045-1

[36] Shakhovska, N., Yakovyna, V., Chopyak, V.: A new hybrid ensemble machine-learning model for severity risk assessment and post-COVID prediction system. Mathematical Biosciences and Engineering 19(6), 6102–6123 (2022). https://doi.org/10.3934/mbe.2022285

[35] Yakovyna, V., Shakhovska, N.: Software failure time series prediction with RBF, GRNN, and LSTM neural networks. Procedia Computer Science 207, 837–847 (2022). https://doi.org/10.1016/j.procs.2022.09.139

[34] Goździejewska A.M., Kruk, M. 2022. Zooplankton network conditioned by turbidity gradient in small anthropogenic reservoirs. Scientific Reports 12:3938. https://doi.org/10.1038/s41598-022-08045-y. 4.996 IF

[33] Kruk, M., Goździejewska, A.M., Artiemjew P. 2022. Predicting the efects of winter water warming in artifcial lakes on zooplankton and its environment using combined machine learning models. Scientific Reports 12:16145. https://doi.org/10.1038/s41598-022-20604-x. 4.996 IF

[32] R. Grycuk, M. Korytkowski, R. Scherer, P. Drozda, W. Wei, M. Kordos, Fast Solar Image Retrieval and Classification by Fuzzy Rules. FUZZ-IEEE 2022: 1-7 (140 pkt)

[31] Krzywicki, T. (2022) Systemy uczące się: uczenie głębokie i głębokie sieci neuronowe.

[30] M. Bocheński, P. Jastrzȩbski, A. Tralle, Homogeneous spaces of real simple Lie groups with proper actions of non virtually abelian discrete subgroups: A computational approach, Journal of Symbolic Computation, Vol.113, 2022, p. 171-180.

[29] Artiemjew, P., Ropiak, K.: 'A Novel Ensemble Model - The Random Granular Reflections', Fundamenta Informaticae, 1 Jan. 2021, vol. 179, no. 2, pp. 183-203, 2021(DOI: 10.3233/FI-2021-2020)

[28] Kruk M., P., Artiemjew , E., Paturej. 2021. The application of game theory-based machine learning modelling to assess climate variability effects on the sensitivity of lagoon ecosystem parameters. Ecological Informatics 66: 101462. doi.org/10.1016/j.ecoinf.2021.101462. 4.498 IF

[27]Krzywicki, T. (2021). Selected Image Analysis Methods for Ophthalmology. In: Grzybowski, A. (eds) Artificial Intelligence in Ophthalmology. Springer, Cham. https://doi.org/10.1007/978-3-030-78601-4_6 (20 pt)

[26] Yakovyna, V., Symets, I.: Reliability assessment of CubeSat nanosatellites flight software by high-order Markov chains. Procedia Computer Science 192, 447–456 (2021). https://doi.org/10.1016/j.procs.2021.08.046

[25] Shakhovska N., Yakovyna V. (2021) Feature Selection and Software Defect Prediction by Different Ensemble Classifiers. In: Strauss C., Kotsis G., Tjoa A.M., Khalil I. (eds) Database and Expert Systems Applications. DEXA 2021. Lecture Notes in Computer Science, vol 12923, pp. 307–313. Springer, Cham. https://doi.org/10.1007/978-3-030-86472-9_28

[24] Yakovyna, V., Shakhovska, N.: Modelling and predicting the spread of COVID-19 cases depending on restriction policy based on mined recommendation rules. Mathematical Biosciences and Engineering 18(3), 2789–2812 (2021). https://doi.org/10.3934/mbe.2021142

[23] M. Bocheński, P. Jastrzębski, A. Szczepkowska, A. Tralle, A. Woike, Semisimple subalgebras in simple Lie algebras and a computational approach to the compact Clifford-Klein forms problem, Experimental Mathematics, 2021, VOL. 30, NO. 1, 86–94.

[22] Kruk M., Paturej E., Artiemjew P. 2020. From explanatory to predictive network modeling of relationships among ecological indicators in the shallow temperate lagoon. Ecological Indicators 117, 106637. 4,490 IF

[21] Aleksander Denisiuk: On range condition of the tensor x-ray transform in Rⁿ, Inverse Problems & Imaging, Vol. 14, No. 3, 423–435, (2020)

[20] M. Bocheński, P. Jastrzębski, A. Tralle, Non-existence of standard compact Clifford-Klein forms of homogeneous spaces of exceptional Lie groups, Math. Comp. 89 (2020), 1487-1499.

[19] Shakhovska N., Yakovyna V., Kryvinska N. (2020) An Improved Software Defect Prediction Algorithm Using Self-Organizing Maps Combined with Hierarchical Clustering and Data Preprocessing. In: Hartmann S., Küng J., Kotsis G., Tjoa A.M., Khalil I. (eds) Database and Expert Systems Applications. DEXA 2020. Lecture Notes in Computer Science, vol. 12391, pp. 414–424. Springer, Cham. https://doi.org/10.1007/978-3-030-59003-1_27

[18] Krzywicki, T. (2019). Application of Meta-Learning Methods in Recognition of Drums on the Basis of Short Soundsamples. Short paper in Proceedings of the 28th International Workshop on Concurrency, Specification and Programming

[17] M.K. Chakraborty, S. Dutta, Theory of Graded Consequence: A General Framework for Logics of Uncertainty, Springer Asia (2019) DOI 10.1007/978-981-13-8896-5.

[16] S. Dutta, A. Skowron, M.K. Chakraborty, Information Flow in Logic for Distributed
Systems: Extending Graded Consequence, Information Sciences 491, 232-250, (2019),
DOI 10.1016/j.ins.2019.03.057; IF(2019): 5.910; Web of Science)

[15] Dutta S., Rozenberg G., Jankowski A., Skowron A., Reaction Systems in Light
of Rough Sets: Toward Linking Abstract Modelling with Physical Reality, Funda-
menta Informaticae 165, 283-302, (2019), DOI: 10.3233/FI-2019-1786. (Web of
Science)

[14] S. Dutta, A. Skowron, Concepts Approximation Through Dialogue With User,
IJCRS 2019, LNCS 11499, pp. 295-311, (2019), DOI 10.1007/978-3-030-22815-6_23.

[13] Aleksander Denisiuk: Reconstruction in the cone-beam vector tomography with
two sources, Inverse Problems, Vol. 34, No. 12, 124008, (2018)

[12] Aleksander Denisiuk, Michał Grabowski: Embedding of the Hamming space into
a sphere with weighted quadrance metric and c-means clustering of nominal-
continuous data, Intelligent Data Analysis, Vol. 22, No. 6, 1297-1314, (2018)

[11] Krzywicki, T. (2018). Weather and a part of day recognition in the photos using a KNN methodology. In Technical Sciences 21(4). Pages: 291-302.

[10] Ślęzak D., Dutta S., Dynamic and Discernibility Characteristics of Different At-
tribute Reduction Criteria, In IJCRS 2018 proceedings, Hung Son Nguyen et al.
(eds), LNCS 11903, pp. 628-643, Springer, Heidelberg, (2018), DOI 10.1007/978-
3-319-99368-3_49. (Web of Science)

[9] S. Dutta, A. Skowron, Bipolar Queries With Dialogue: Rough Set Semantics, In
IJCRS 2018 proceedings, Hung Son Nguyen et al. (eds), LNCS 11903, 229-242,
(2018), DOI 10.1007/978-3-319-99368-3_18; Web of Science.

[8] S. Dutta, P. Wasilewski, Dialogue in Concept Hierarchical Learning using Proto-
types and Counterexamples, Fundamenta Informatica 162, pp. 17-36, (2018), DOI:
10.3233/FI-2018-1711; IF(2018): 1.204; Web of Science.

[7] Volochiy, B., Yakovyna, V., Mulyak, O., Kharchenko, V.: Availability model of critical nuclear power plant instrumentation and control system with non-exponential software update distribution. In: N. Bassiliades, V. Ermolayev, H.-G. Fill, V. Yakovyna, H. C. Mayr, M. Nikitchenko, G. Zholtkevych, A. Spivakovsky (eds.), Communications in Computer and Information Science, CCIS 826 (2018), Springer, pp. 3–20. https://doi.org/10.1007/978-3-319-76168-8_1

[6] Volochiy, B., Yakovyna, V., Mulyak, O.: Analytical Model for Availability Assessment of IoT Service Data Transmission Subsystem. In: N. Shakhovska and V. Stepashko (eds.), Advances in Intelligent Systems and Computing II, AISC 689 (2018), Springer, pp. 588–600. https://doi.org/10.1007/978-3-319-70581-1_41

[5] Dutta S., Esteva F., Godo L., On a Three-valued Logic to Reason with Prototypes
and Counterexamples and a Similarity-based Generalization, In Advances in Artifi-
cial Intelligence, O. Luaces et al. (Eds.): CAEPIA 2016, LNAI 9868, Springer, Hei-
delberg,(2016), pp. 498-508, DOI 10.1007/978-3-319-44636-3_47.

[4] L. Polkowski, P. Artiemjew: Granular Computing in Decision Approximation, An Application of Rough Mereology, In: Series: Intelligent Systems Reference Library, Vol. 77, 452 pages, Springer (2015)

[3] K.Sopyła, P. Drozda, Stochastic Gradient Descent with Barzilai-Borwein Update Step for SVM Purposes, Information Sciences, Elsevier, p. 218 - 233, 2015 (teraz chyba 200 pkt - wcześniej 45 pkt starej punktacji)

[2] S. Dutta, B.R.C. Bedregal, M.K. Chakraborty, Some Instances of Graded Consequence in the Context of Interval-valued Semantics, In Logic and Applications, M.Banerjee, Krishna S. (eds), LNCS 8923, pp. 74-87, (2015), DOI 10.1007/978-3-662-45824-2_5; Web of Science.

[1] M. Bocheński, P. Jastrzębski, A. Tralle, Stretched non-positive Weyl connections on solvable Lie groups, Annali di Matematica Pura ed Applicata, 2013.