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Ing. Marek Ružička, PhD.

Ing. Marek Ružička, PhD.

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Dr. Marek Ružička is an Assistant Professor at the Department of Computers and Informatics at the Technical University of Košice. He completed his doctoral studies under the mentorship of Professor Ing. Juraj Gazda, PhD., focusing on the application of machine learning principles within dynamic Radio Access Network (RAN) operators' networks. Marek Ružička's research primarily concentrates on implementing deep learning technologies in 5G dynamic RAN networks. He is actively developing advanced techniques to enhance the efficiency of algorithms for positioning UAV-mounted base stations, with a particular emphasis on energy efficiency. In 2021, he enriched his expertise through an internship at the Czech Technical University in Prague, where he contributed to the 6G mobile research laboratory.

His current research endeavors include exploring Physics-Informed Neural Networks (PINNs) for practical applications. The insights gained from this research have been instrumental in developing the online AI-powered simulator siml.ai.

Research interests:
  • UAVs
  • Deep Learning
  • 5G
  • Dynamic RAN
  • Physics-Informed Neural Networks
Publications:

2024

M. Muzelak, T. Škovránek, M. Ružička

Physics-Informed Neural Networks Application To Mass-Spring System Solution

Journal: 2024 25th International Carpathian Control Conference

F. Adjailia, D. Jopek, M. Takáč, M. Ružička, S. Haddaoui

Simulation analysis of car aerodynamics within tunnel environment using deep learning: a comparative architectural study

Journal: 2024 6th International Conference on Pattern Analysis and Intelligent Systems.

2023

M. Ružička, M. Dopiriak

Clustering Using Conditional Generative Adversarial Networks (cGANs)

Journal: Radioelektronika 2023.

M. Ružička, Z. Bečvář, J. Gazda

Energy Consumption Optimization for UAV Base Stations With Wind Compensation

Journal: IEEE Communications Letters.

2022

M. Ružička, T. Maksymyuk, J. Gazda, M. Vološin, Y. Bobalo

Correcting defective trajectories using conditional gan

Journal: 2021 IEEE 4th International Conference on Advanced Information and Communication Technologies

M. Ružička, M. Vološin, J. Gazda, T. Maksymyuk, L. Han, M. Dohler

Fast and computationally efficient generative adversarial network algorithm for unmanned aerial vehicle–based network coverage optimization

Journal: International Journal of Distributed Sensor Networks.

2021

M. Ružička, M. Vološin, J. Gazda, T. Maksymyuk

Deep Learning-Based Blockchain Framework for the COVID-19 Spread Monitoring

Journal: International conference on Electrical, computer, communications and mechatronics engineering.

2020

T. Maksymyuk, J. Gazda, M. Ružička, E. Šlapak, G. Bugár, H. Longzhe

Deep Learning based Mobile Network Management for 5G and Beyond

Journal: IEEE 15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering.

M. Ružička, M. Vološin, J. Gazda, T. Maksymyuk

The extension of existing end-user mobility dataset based on generative adversarial networks

Journal: Radioelektronika 2020

2019