Doctoral studies / Doctoral programmes / Process control
A PhD. graduate in Process Control is a highly qualified expert with advanced knowledge and research skills in modern process control, automation, digitalization, and intelligent systems. Graduates possess a strong interdisciplinary background that enables them to conduct cutting-edge research and innovation in areas such as process modelling and control, cyber-physical systems, robotics and mechatronics, as well as software and communication architectures for complex control systems. The programme allows graduates to further specialize in intersecting and emerging fields, including artificial intelligence, adaptive and cognitive systems, intelligent communication, and safety-critical control applications, reflecting current industrial and societal needs. Graduates master scientific methods of basic and applied research in cybernetics and automation. They are capable of independent critical thinking, abstraction, and synthesis, and of developing new concepts, methodologies, and solutions. They independently design and conduct research with a high level of scientific integrity, translating theoretical and experimental results into practical, real-world applications. Their original research contributes to the advancement of scientific knowledge and is suitable for publication in international peer-reviewed journals and conferences. PhD graduates are also trained to communicate complex ideas effectively, both to expert audiences and the broader public, and to lead or collaborate within multidisciplinary research teams.
Graduates design, coordinate, and validate innovative cyber-physical and automated systems, ensuring compliance with safety, reliability, and security standards. They are well prepared for careers in academic research, advanced industrial development, and high-technology sectors, fully aligned with the third (doctoral) level of higher education in cybernetics.
Návrh metodiky pre inteligentné a prediktívne riadenie
priemyselných pohonov s využitím Edge-based analýzy dát
Gabriel Gašpar
Prediktívna údržba prvkov železničných zabezpečovacích systémov s
využitím modelov a rozhodovacích algoritmov
Jozef Hrbček
Návrh využitia heterogénnych Big Data zdrojov pre riadenie procesov
Juraj Ďuďák
Bezpečné vyhodnotenie obrazu
Juraj Ždánsky
Využitie metód UI pre návrh adaptívneho SLAM systému pre all-weather
lokalizáciu
Marián Hruboš
Kybernetická bezpečnosť IoT a embedded zariadení
Peter Vestenický
Digitálne dvojča mestských systémov s implementáciou metód umelej
inteligencie pre včasnú detekciu kybernetických útokov
Rastislav Pirník
Zvyšovania kybernetickej odolnosti OT systémov
Rastislav Pirník
Výskum využitia nástrojov umelej inteligencie pri fúzii dát zo snímačov v
doprave
Vojtech Šimák
Výskum využitia autonómnej kooperácie UGV a UAV
Vojtech Šimák
Gabriel Gašpar
Jozef Hrbček
Marián Hruboš
Aleš Janota
Dušan Nemec
Rastislav Pirník
Karol Rástočný
Anna Simonová
Vojtech Šimák
Peter Vestenický
Juraj Ždánsky