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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:

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.

M. Ružička

Learning turbulent flows with neural network

Journal: 23rd Scientific Conference of Young Researchers

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

Energy consumption of UAV when hovering

Journal: 22nd Scientific Conference of Young Researchers

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.

M. Ružička

Synthetic End-user Trajectory Generation

Journal: 21st Scientific Conference of Young Researchers.

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

M. Ružička, M. Chovanec

Application of the machine learning principles in the sports betting systems

Journal: Acta Electrotechnica et Informatica.