Our Team

Roman Senkerik received his Ph.D. degree in Technical Cybernetics from the Tomas Bata University in Zlin, Czech Republic in 2008. He is currently a full professor at the Tomas Bata University in Zlin, Faculty of Applied Informatics. His research interests include interdisciplinary applications of evolutionary computation, modification and development of evolutionary and swarm based algorithms, computational intelligence, optimization, cyber-security, theory of chaos, emergence and complexity.

1. Zelinka, I., Lampinen, J., Senkerik, R., & Pluhacek, M. (2015). Ivestigatio o evolutioary algorithms powered by oradom processes. Soft Computing, 1-11.
2. Senkerik, R., Kominkova Oplatkova, Z., Zelinka, I., Chramcov, B., Davendra, D. D., & Pluhacek, M. (2014). Utilization of analytic programming for the evolutionary synthesis of the robust multi-chaotic controller for selected sets of discrete chaotic systems. Soft Computing, 18(4), 651-668.
3. Kominkova Oplatkova, Z.., Senkerik, R., Zelinka, I., & Pluhacek, M. (2013). Analytic programming in the task of evolutionary synthesis of a controller for high order oscillations stabilization of discrete chaotic systems. Computers & Mathematics with Applications, 66(2), 177-189.
4. Senkerik, R., Oplatkova, Z., Zelinka, I., & Davendra, D. (2013). Synthesis of feedback controller for three selected chaotic systems by means of evolutionary techniques: Analytic programming. Mathematical and Computer Modelling, 57(1-2), 57-67.
5. Zelinka, I., Chadli, M., Davendra, D., Senkerik, R., & Jasek, R. (2013). An investigation on evolutionary reconstruction of continuous chaotic systems. Mathematical and Computer Modelling, 57(1-2), 2-15.
6. Senkerik, R., Davendra, D., Zelinka, I., Oplatková, Z., & Jasek, R. (2012). Performance comparison of differential evolution and SOMA on chaos control optimization problems. International journal of bifurcation and chaos, 22(08), 1230025.
7. Senkerik, R., Zelinka, I., Davendra, D., & Oplatkova, Z. (2010). Utilization of SOMA and differential evolution for robust stabilization of chaotic Logistic equation. Computers & Mathematics with Applications, 60(4), 1026-1037.
8. Zelinka, I., Senkerik, R., & Navratil, E. (2009). Investigation on evolutionary optimization of chaos control. Chaos, Solitons & Fractals, 40(1), 111-129.

Zuzana Kominkova Oplatkova received her Ph.D. degree in Technical Cybernetics in 2008 at Tomas Bata University in Zlín, Faculty of Applied Informatics, Czech Republic. She works at the same university since 2004, currently as a full professor. This title has been awarded to her at Tomas Bata University in Zlín in 2023. She serves as a member of journal editorial boards, member of conference international programme committees, journal reviewer and guest editor of books published by Springer. She had lectures at 12 European universities under the programme Erasmus. Her research interests include evolutionary computation, artificial neural networks, chaos control, classification techniques, pseudo neural networks and evolutionary symbolic regression methods.

Adam Viktorin was born in the Czech Republic in 1989, and went to the Faculty of Applied Informatics at Tomas Bata University in Zlín, where he studied Computer and Communication Systems and obtained his MSc degree in 2015. He obtained his Ph.D. degree at the same University in 2021 with the thesis topic: Control Parameter Adaptation in Differential Evolution. Among his professional interests are: development and analysis of adaptive strategies for Differential Evolution in the area of numerical optimization; and also application of such algorithms to real-world problems.

1. A. Viktorin, R. Senkerik, M. Pluhacek, T. Kadavy, A. Zamuda, Distance based parameter adaptation for Success-History based Differential Evolution, Swarm Evol. Comput. 50 (2019) 100462. doi:10.1016/J.SWEVO.2018.10.013.
2. Viktorin, A., Senkerik, R., Pluhacek, M., & Kadavy, T. (2017). Modified progressive random walk with chaotic PRNG. International Journal of Parallel, Emergent and Distributed Systems, 1-10.
3. Viktorin, A., Pluhacek, M., & Senkerik, R. (2016, June). Multi-chaotic system induced success-history based adaptive differential evolution. In International Conference on Artificial Intelligence and Soft Computing(pp. 517-527). Springer, Cham.
4. Viktorin, A., Senkerik, R., Pluhacek, M., & Zamuda, A. (2016, December). Steady success clusters in Differential Evolution. In Computational Intelligence (SSCI), 2016 IEEE Symposium Series on(pp. 1-8). IEEE.
5. Viktorin, A., Pluhacek, M., & Senkerik, R. (2016, September). Network based linear population size reduction in SHADE. In Intelligent Networking and Collaborative Systems (INCoS), 2016 International Conference on(pp. 86-93). IEEE.

Anezka Kazikova researches the development process of new metaheuristics and the challenges it brings. Her main focus is to promote good practice in benchmarking. In her doctoral thesis she proposed guidelines for developers of new metaheuristics and applied these guidelines to her own development project the Bison Algorithm. She received her Ph.D. degree in Engineering Informatics at Tomas Bata University in Zlin in 2022.

1. Kazikova, A., Development and Modification of Modern Bio-Inspired Swarm Algorithms. Zlin, 2022. Available from: https://theses.cz/id/3e6cis/ . Doctoral thesis. Tomas Bata University in Zlin, Faculty of Applied Informatics. Supervisor doc. Ing. Roman Senkerik, Ph.D.
2. Kazikova, A., Pluhacek, M., & Senkerik, R. (2021). How does the number of objective function evaluations impact our understanding of metaheuristics behavior?. IEEE Access, 9, 44032-44048., doi: 10.1109/ACCESS.2021.3066135.
3. Kazikova, A., Łapa, K., Pluhacek, M., & Senkerik, R. (2020, October). Cascade PID Controller Optimization Using Bison Algorithm. In International Conference on Artificial Intelligence and Soft Computing (pp. 406-416). Springer, Cham.
4. Kazikova, A., Pluhacek, M., Senkerik, R., & Viktorin, A. (2017, June). Proposal of a new swarm optimization method inspired in bison behavior. In 23rd International Conference on Soft Computing (pp. 146-156). Springer, Cham.
5. Kazikova, A., Pluhacek, M., Viktorin, A., & Senkerik, R. (2018, June). New Running Technique for the Bison Algorithm. In International Conference on Artificial Intelligence and Soft Computing (pp. 417-426). Springer, Cham
6. Kazikova, A., Pluhacek, M., & Senkerik, R. (2020, December). Why Tuning the Control Parameters of Metaheuristic Algorithms Is So Important for Fair Comparison?. In Mendel (Vol. 26, No. 2, pp. 9-16). DOI: https://doi.org/10.13164/mendel.2020.2.009.

Alzbeta is a PhD student of Artificial Intelligence department at Tomas Bata University in Zlin under the supervision of assoc. Prof. Zuzana Kominkova Oplatkova. She studied Biomedical Engineering at Brno University of Technology and finished her master’s studies in 2015. Then she started her doctoral studies in Zlin. In her research, she focus on Computer Vision and Image Processing, especially the usage of these technologies in medicine.

1. Tureckova, A., & Rodríguez-Sánchez, A. J. (2018, September). ISLES Challenge: U-Shaped Convolution Neural Network with Dilated Convolution for 3D Stroke Lesion Segmentation. In International MICCAI Brainlesion Workshop (pp. 319-327). Springer, Cham.
2. Vlachynska, A., Oplatkova, Z. K., & Turecek, T. (2018, April). Dogface detection and localization of dogface’s landmarks. In Computer Science On-line Conference (pp. 465-476). Springer, Cham.
3. Vlachynska, A., Oplatkova, Z. K., & Sramka, M. (2017, July). The coordinate system of the eye in cataract surgery: Performance comparison of the circle Hough transform and Daugman’s algorithm. In AIP Conference Proceedings (Vol. 1863, No. 1, p. 070037). AIP Publishing.
4. Vlachynska, A., Cerveny, J., Cmiel, V., & Turecek, T. (2016, April). Automatic image-based method for quantitative analysis of photosynthetic cell cultures. In International Conference on Hybrid Artificial Intelligence Systems (pp. 402-413). Springer, Cham.

Tomas Kadavy was born in the Czech Republic in 1990, and went to the Faculty of Applied Informatics at Tomas Bata University in Zlin, where he studied Information Technologies and obtained his MSc degree in 2016. He is studying his Ph.D. at the same University and the fields of his studies are: swarm based algorithms, computational intelligence and optimization.

1. Kadavy, T., Pluhacek, M., Viktorin, A., & Senkerik, R. (2017). Partial Population Restart of Firefly Algorithm Using Complex Network Analysis. In IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings (pp. 2505-2511). New Jersey.
2. Kadavy, T., Pluhacek, M., Viktorin, A., & Senkerik, R. (2017). Firework algorithm dynamics simulated and analyzed with the aid of complex network. In Proceedings-31st European Conference on Modelling and Simulation, ECMS 2017. European Council for Modelling and Simulation.
3. Kadavy, T., Pluhacek, M., Viktorin, A., & Senkerik, R. (2017, June). Hypersphere Universe Boundary Method Comparison on HCLPSO and PSO. In International Conference on Hybrid Artificial Intelligence Systems(pp. 173-182). Springer, Cham.
4. Kadavy, T., Pluhacek, M., Viktorin, A., & Senkerik, R. (2017, June). Comparing strategies for search space boundaries violation in PSO. In International Conference on Artificial Intelligence and Soft Computing(pp. 655-664). Springer, Cham.

Luis Antonio Beltrán Prieto was born in Mexico in 1983. He obtained his bacherlor’s degree in Computer Science at Instituto Tecnológico de Celaya in 2006 and became a lecturer at the same university two years later. He is currently doing his PhD at Tomas Bata University in Zlín. His research fields include artificial intelligence, deep learning, artificial neural networks, and machine learning. During his free time, he enjoys developing and learning about mobile applications connected to the cloud which make use of cognitive, smart capabilities, as well as sharing his knowledge with other fellow developers from around the world.

Michal Pluhacek Received his Ph.D. degree in Information Technologies from the Tomas Bata University in Zlin, the Czech Republic in 2016 with the dissertation topic: Modern method of development and modifications of evolutionary computational techniques. Currently works as a researcher at the Regional Research Centre CEBIA-Tech of Tomas Bata University in Zlin. He is the author of many journal and conference papers on Particle Swarm Optimization and related topics. His research focus includes swarm intelligence theory and applications and artificial intelligence in general. In 2019, he finished six-months long research stay at New Jersey Institute of Technology, USA, focusing on swarm intelligence and swarm robotics. He became an assoc. prof. in 2023 after successfully defending his habilitation thesis on the topic „Inner Dynamics of Evolutionary Computation Techniques: Meaning for Practice.“

1. Pluhacek, M., Senkerik, R., & Zelinka, I. (2014). Particle swarm optimization algorithm driven by multichaotic number generator. Soft Computing, 18(4), 631-639.
2. Pluhacek, M., Senkerik, R., Davendra, D., Oplatkova, Z. K., & Zelinka, I. (2013). On the behavior and performance of chaos driven PSO algorithm with inertia weight. Computers & Mathematics with Applications, 66(2), 122-134.
3. Pluhacek, M., Senkerik, R., & Davendra, D. (2015). Chaos particle swarm optimization with Eensemble of chaotic systems. Swarm and Evolutionary Computation, 25, 29-35.
4. Pluhacek, M., Senkerik, R., Viktorin, A., Kadavy, T., & Zelinka, I. (2017, December). A review of real-world applications of particle swarm optimization algorithm. In International Conference on Advanced Engineering Theory and Applications (pp. 115-122). Springer, Cham.
5. Pluhacek, M., Viktorin, A., Senkerik, R., Kadavy, T., & Zelinka, I. (2017, June). PSO with partial population restart based on complex network analysis. In International Conference on Hybrid Artificial Intelligence Systems (pp. 183-192). Springer, Cham.