Personal statement

I trained as a chemical engineer and became a systems and data scientist. One question links my work across three decades: how can we understand a complex system, make its processes measurable, create feedback – and improve it? I have applied this loop to chemical processes, to manufacturing and human–machine systems, to a university and to a region. Next, I focus on systems in which people and AI agents work together.

1 · Knowledge generation

Interpretable fuzzy and data-driven models, clustering-based system identification, network controllability and observability, and human-centred Industry 4.0/5.0. Five selected outputs:

Fuzzy Model Identification for Control (Birkhäuser, 2003) · Cluster Analysis for Data Mining and System Identification (with B. Feil, Birkhäuser, 2007) · Controllability and observability in complex networks (Scientific Reports, 2017, open access) · Enabling Technologies for Operator 4.0 (Applied Sciences, 2018, open access) · From Operator 4.0 towards Operator 5.0 (Journal of Manufacturing Systems, 2023, open access)

2 · Developing people

23 doctoral graduates supervised or co-supervised; alumni lead R&D, data and engineering teams at companies such as MOL Group, Borealis, Wizz Air, SAP and ZEISS, and in academia. Founder and first programme leader of postgraduate programmes in automotive quality management (2013, with Continental), Industry 4.0 and AI solutions; programme leader of the Industrial Systems Engineering MSc. Master Teacher Gold Medal (2023).

3 · Research community and leadership

Rector of the University of Pannonia (2024–2029); earlier vice-rector, vice-dean for research and for education, institute director and head of department. Founder of the MTA–PE Lendület group (2017–2022, rated excellent) and head of its HUN-REN–PE successor (2022–2027). Editorial work for Sensors and Applied Soft Computing; 75+ international programme committees; partners include TU Delft, Warsaw University of Technology, Tecnológico de Monterrey and the University of Southern Denmark.

4 · Society and innovation

Industrial R&D from soft sensors, HAZOP and alarm management to process mining (BorsodChem, Dunaferr, TVK, MOL/Slovnaft, E.ON; recently Balluff, Foxconn, iQor, Sunstone RTLS). Data-driven regional and policy analysis (iASK Big Data and Complexity Centre, 2015–16); concept of an integrated monitoring system for Lake Balaton; university–city councils in Veszprém, Zalaegerszeg and Nagykanizsa.

5 · Open science

Key results published open access; datasets with DOIs on Mendeley Data and figshare; reusable code such as the Fuzzy Clustering and Data Analysis Toolbox and the NOCAD network toolbox (see Programs and data).

Next 3–5 years

Research: monitoring and trustworthy development of complex human–AI agent systems – observability through event logs, multimodal data and temporal knowledge graphs; provenance, uncertainty and human oversight. Institution: implementing the University of Pannonia’s 2026–2030 development plan, including regulated, auditable use of AI (aligned with ISO/IEC 42001). Society: responsible AI adoption in SMEs and evidence-based regional development.

Profiles: ORCID · Google Scholar · MTMT · Scopus · doktori.hu · LinkedIn · Updated: November 2026