Our Team

Head of the lab

assoc. prof. Roman Senkerik Ph.D.

Department of Informatics and Artificial Intelligence

Contacts:

Research Focus:

  • Computational Intelligence
  • Evolutionary Algorithms
  • Optimization
  • Chaos Theory
Short Bio

Roman Senkerik received his Ph.D. degree in Technical Cybernetics from the Tomas Bata University in Zlin, Czech Republic in 2008. He is currently an associated 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.

Selected publications
  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.
Senior Researcher

assoc. prof. Zuzana Kominkova Oplatkova Ph.D.

Department of Informatics and Artificial Intelligence

Contacts:

Research Focus:

  • Artificial Intelligence
  • Soft Computing
  • Evolutionary Symbolic Regression – Analytic Programming
  • Pseudo Neural Nets & Artificial Neural Nets
Short Bio

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 an associate professor. This title has been given to her at Brno Technical University, Faculty of Information Technologies in June 2013. She serves as an member of journal editorial boards, member of conference international programme committees, journal reviewers 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.

Selected publications
  1. 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.
  2. Volná, E., Kotyrba, M., Kominkova Oplatkova, K., & Senkerik, R. (2016). Elliott waves classification by means of neural and pseudo neural networks. Soft Computing, 1-11.
  3. Afful-Dadzie, E., Afful-Dadzie, A., & Kominkova Oplatkova, Z. (2014). Measuring progress of the millennium development goals: A fuzzy comprehensive evaluation approach. Applied artificial intelligence, 28(1), 1-15.
  4. Komínkova Oplatkova, Z., & Senkerík, R. (2016). Pseudo neural networks synthesized via evolutionary symbolic regression for Pima diabetes. MENDEL 2016.
  5. Meli, C., & Kominkova Oplatkova, Z. (2016). SPAM detection: Naïve bayesian classification and RPN expression-based LGP approaches compared. In Software Engineering Perspectives and Application in Intelligent Systems (pp. 399-411). Springer, Cham.

Junior Researcher

Ing. Michal Pluhacek Ph.D.

Regional Research Centre CEBIA-Tech

Contacts:

Research Focus:

  • Swarm Intelligence
  • Particle Swarm Optimization
  • Adaptive Techniques for Swarm Algorithms
  • Swarm Robotics
Short Bio

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 junior researcher at the Regional Research Centre CEBIA-Tech of Tomas Bata University in Zlin. His research focus includes swarm intelligence theory and applications and artificial intelligence in general. In 2019 finished six-months long research stay at New Jersey Intitute of Technology, USA focusing on swarm robotics.

Selected publications
  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.

Ph.D. student

Ing. Adam Viktorin

Department of Informatics and Artificial Intelligence

Contacts:

Research Focus:

  • Artificial Intelligence
  • Adaptive strategies for Differential Evolution
  • Running around
Short Bio

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 is studying his Ph.D. at the same University and the fields of his studies are: Artificial Intelligence, Data Mining and Evolutionary Computation. His most recent professional “hobby” is a development and analysis of self-adaptive strategies for Differential Evolution in the area of numerical optimization; and also application of such algorithms to real-world problems.

  Selected publications
  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. Viktorin, A., Senkerik, R., Pluhacek, M., & Kadavy, T. (2017, December). L-SHADE algorithm with distance based parameter adaptation. In International Conference on Advanced Engineering Theory and Applications(pp. 69-80). Springer, Cham.

Ph.D. student

Ing. Alzbeta Tureckova

Department of Informatics and Artificial Intelligence

Contacts:

Research Focus:

  • Computer Vision
  • Image Processing
  • Biomedicine
Short Bio

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.

  Selected publications
  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.

Ph.D. student

Ing. Tomas Turecek

Department of Computer and Communication Systems

Contacts:

Research Focus:

  • Time Series Analysis

Ph.D. student

Ing. Tomas Kadavy

Department of Informatics and Artificial Intelligence

Contacts:

Research Focus:

  • Swarm Intelligence
  • Modern Swarm Algorithms and their Application
  • Coffeeeee
Short Bio

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.

Selected publications
  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.

Ph.D. student

Ing. Anezka Kazikova

Department of Informatics and Artificial Intelligence

Contacts:

Research Focus:

  • Swarm Algorithms
  • Optimization
  • Metaheuristics
Short Bio

Anezka is a PhD student of the Artificial Intelligence Department at Tomas Bata University in Zlin. She graduated the Engineering Informatics at Tomas Bata University with honours in 2015 and was awarded by the Dean’s Award in 2015 and the EdHouse Award in 2013 for her Master’s and Bachelor’s Theses. As she had always been denied to the carry out experiments on real animals, she had to settle for simulations. In 2017 she developed the Bison Algorithm optimization with nonnegligible help from the A.I.Lab and they keep on running ever since.

Ph.D. student

MSc. Luis Antonio Beltran Prieto

Department of Informatics and Artificial Intelligence

Contacts:

Research Focus:

Short Bio

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.