Members of the
Industry 5.0 laboratory

Tamás Ruppert - Head of research lab

Tamas is an Associate Professor at the Department of Process Engineering at the University of Pannonia. He graduated with bachelor's (2015) degree in Mechanical Engineering and (2015) in Engineering Information Technology and master's (2016) degree Mechatronic Engineering and received PhD degrees in 2020. His current research focuses on Operator 4.0, and his research interest covers the areas of activity recognition, discrete-event simulators, and human-centric solutions. 

János Abonyi - Head of research group

Janos is a full professor at the Department of Process Engineering at the University of Pannonia in computer science and chemical engineering. He received MEng and PhD degrees in chemical engineering in 1997 and 2000 from the University of Veszprem, Hungary. In 2008, he earned his Habilitation in the field of Process Engineering, and the DSc degree from the Hungarian Academy of Sciences in 2011. In the period of 1999-2000 he was employed at the Control Laboratory of the Delft University of Technology (in the Netherlands). Dr. Abonyi has co-authored more than 250 journal papers and chapters in books and has published five research monographs and one Hungarian textbook about data mining. His research interests include complexity, process engineering, quality engineering, data mining and business process redesign.

Abdulrahman K. E. Al-Sabaawi

Abdulrahman graduated with bachelor's degree B.Eng in Medical Instrumentation Technology Engineering at the Northern Technical University, Iraq in 2011 and my master's degree MSc in Biomedical Engineering at the University of Strathclyde, UK in 2015. The MSc’s project was about studying human emotions through recording the Galvanic Skin Response (GSR). I am a PhD student at the Department of Processing Engineering/University of Pannonia through the Stipendium Hungaricum Scholarship. My main PhD research field is in human intention recognition and Bio-signal processing. We will focus on monitoring cognitive load on human through recording specific physiological signals; GSR at the first step and Heart Rate Variability (HRV) in the second step.

András Darányi

András graduated with a bachelor's degree in biochemical engineering (2018) and a master's degree in engineering management (2020). He is a Ph.D. student at the University of Pannonia, supervised by Dr. Tamás Ruppert and Dr. János Abonyi. His research topic is the support of tool management with machine learning algorithms, which includes tool monitoring, allocation, and maintenance. His current research focuses on extracting valuable data and mobility patterns from indoor position data by processing with probability-based clustering algorithms and sequential Monte Carlo state estimation. 

Tímea Czvetkó

Tímea graduated with bachelor's (2020) degree in technical management, and master's degrree in engineering management (2022) at the university of Pannonia. She recieved a postgraduate degree in research and innovation management (2020) and Industry 4.0 solution developments and data and systems science (2022) at the University of Pannonia. Her research interest covers the area of Industry 5.0, sustainability problems, human-centred development, business process and regional development.

Mónika Gugolya

Mónika is pursuing a bachelor's degree in mechatronics engineering. Her current research includes collaborative work scheduling between humans and robots and optimisation.  

Gergely Halász

Gergely graduated with bachelor's (2023) and currently pursuing master’s degree in mechatronics engineering. His current research interests include Operator 4.0 and human-centric solutions. 

Judit Horváth

Judit is pursuing a bachelor's degree in computer programming at University of Pannonia. She's current research focuses on optimization of machine maintenance.

Zoltán Jeskó

Zoltán graduated with a bachelor's (2020) and master's (2023) degree in mechatronic engineering. He has worked as a quality engineer in the manufacturing industry in Hungary and is currently working in Germany as a process engineer supporting  operational manufacturing processes. His current research focuses on the qualitative and quantitative measurement of operator performance and the impact of workload.

Tibor Medvegy

Tibor is an Assistant Professor at University of Pannonia, Research Centre for Engineering Sciences. He graduated with master's degree in physics education at University of Szeged (2011), and received PhD degree in physics at Eötvös Loránd University (2017). His research interest covers the areas of sensor- and measurement technology. 

Tuan-anh Tran

Tuan-anh graduated with a bachelor's (2015) degree in mechanical engineering in Vietnam, and a master's (2019) degree in technical management in Hungary. He has worked as a Lean consultant in the Vietnamese manufacturing industry and participated in multiple improvement projects regarding productivity, quality, and safety. His current research interest is data analysis in manufacturing operational management from a system engineering aspect, to facilitate the Operator 4.0 application and Lean 4.0 transformation. 

Vera Varga

Vera is an Assistant Professor at the Institue of Psychology and Mental Hygiene, University of Pannonia. She graduated with master's degree in psychology at the Eötvös Loránd University (2016), and received her PhD degree in psychology at the Budapest University of Technology and Economics (2023). Her research interest is the measurement of cognitive processes via physiological methods.

Former members of the lab

László Nagy

Laszló Nagy received the bachelor’s degree in mechatronics engineering in 2015, the master’s degree in mechatronics engineering, in 2017, and the Ph.D. degree, in 2023. He has five years of experience as an Instrumentation and Controls Field Service Engineer at Siemens, working with industrial gas turbines worldwide. His research interest covers the areas of semantic networks, modeling of manufacturing systems, and development of complex optimization methods. Furthermore, study the industry 5.0, human-centered approach, using knowledge graphs and ontologies.