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Balint Molnar
Eötvös Loránd University of Budapest
Budapest, Hungary

Bálint Molnár is an associate professor at Eötvös Loránd University’s Faculty of Informatics in Budapest, Hungary. He teaches courses on methodologies of information systems development, enterprise resource planning (ERP), integrated systems, web technologies for enterprise information systems, and service science.

Bálint’s research areas include formal and mathematical methods for information systems modeling, ERP systems, complex information systems, business process modeling, the semantic web, enterprise architectures, service-oriented architecture (SOA), service science, and the application of data science methods to the world of information systems. He participates in research projects at the university and supervises several doctoral students. His work on information systems and their formal modeling led to the introduction of hypergraphs and homology into the formal modeling of business processes and information system architecture.

Bálint has published more than 250 papers and serves on the editorial boards for the Electronic Journal of Information Systems Evaluation and the European Journal of Applied Economics. He is a regular reviewer for several scientific conferences and journals, including the Conference on Enterprise Information Systems (CENTERIS), Journal of Computing and Information Technology (CIT), and IEEE Access, and a member of many professional organizations (János Bolyai Mathematical Society, John von Neumann Computer Society, ISACA, the ACM). He formerly worked as a consultant and project manager in the Hungarian Public Administration.

Bálint has been a reviewer for Computing Reviews since 2014. He has written more than 50 reviews.


Logical methods: the art of thinking abstractly and mathematically
Antonsen R., Springer, New York, NY, 2021. 304 pp.  Type: Book (978-3-030637-76-7)

The book, dedicated to undergraduate students just starting their studies, promises a basic grounding in mathematics to be used in computer science (CS) and the related scientific subjects....


Data privacy and trust in cloud computing: building trust in the cloud through assurance and accountability
Lynn T., Mooney J., van der Werff L., Fox G., Palgrave Macmillan, Switzerland, 2021. 170 pp.  Type: Book (978-3-030546-59-5)

The book is a compilation of chapters that investigates issues related to cloud (computing) service providers (CSPs), specifically customer trust and service-level requirements (SLRs). The majority of the chapters (except the last one)...


 Mathematical foundations of big data analytics
Shikhman V., Müller D., Springer International Publishing, New York, NY, 2021. 288 pp.  Type: Book (978-3-662625-20-0), Reviews: (2 of 2)

Data science--and big data analytics as its most recent subdiscipline--is a fashionable research area and teaching subject. Many open-access libraries and source codes provide the opportunity to play with the availabl...


Big data mining for climate change
Zhang Z., Li J., ELSEVIER, Cambridge, MA, 2020. 344 pp.  Type: Book (978-0-128187-03-6)

The book looks more like an encyclopedia than a handbook or textbook. The chapter titles mention climate issues that are typically discussed in the last subsections of the given chapter. Each chapter systematically goes through the for...


Software project estimation: intelligent forecasting, project control, and client relationship management
Dimitrov D., Apress, New York, NY, 2020. 136 pp.  Type: Book (978-1-484250-24-2), Reviews: (2 of 2)

More like a professional handbook than a scientific study, Dimitrov is a practitioner who works on projects as a scrum master and has experience in how to communicate with business people, software designers, and technical and software...


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