Researchers

Principal Investigator

Miklós SEBŐK is a research professor and director at the poltextLAB artificial intelligence laboratory of the HUN-REN Centre of Social Sciences in Budapest. He earned an M.A. degree in politics at the University of Virginia and an M.A. degree in economics at the Corvinus University of Budapest. He received his Ph.D. in Political Science from ELTE University of Budapest. He is also the research director of the Hungarian Comparative Agendas Project and the research co-director of the Artificial Intelligence National Lab at CSS, Budapest. His research interests include political economy, public policy and the application of text mining and machine learning methods in these fields.

Senior Researchers

20220211_185506

Orsolya RING received her Ph.D. in History from ELTE University of Budapest. She is working in the poltextLAB Project on creation and classification of large-scale newspaper corpora and elaboration of a domain-specific method for Hungarian sentiment analysis applying various machine learning methods. She is also working on the building of large-scale historical text corpora and its analysis by NLP methods in the Research Group Computational Social Science (CSS-RECENS).

Molnár Csaba

Csaba MOLNÁR studied political science (BA, MA Corvinus University of Budapest, BA, Nottingham Trent University). He earned a PhD from Corvinus University of Budapest. In the poltextLAB project he is responsible for NLP-related and database building tasks. His main research fields are right-wing radicalism and legislative studies. He also participates in the Hungarian Comparative Agendas Project where he works on legislative database development.

 

István ÜVEGES is a researcher at the HUN-REN Centre for Social Sciences, Political and Legal Text Mining and Artificial Intelligence Laboratory (poltextLAB), and a Computational Linguist at MONTANA Knowledge Management Ltd. He previously earned BSc degree in Computer Science, and MA degree in Theoretical Linguistics. His main interests include practical applications of Automation, Artificial Intelligence (Machine Learning), Computational Propaganda, Legal Language (legalese) studies and the Plain Language Movement.

 

 

   

Young scholars

Martin Balázs BÁNÓCZY is a third-year Computer Science Engineer student specializing in artificial intelligence at Obuda University. His main areas of interest include machine learning, software development and image processing. In his bachelor thesis, he develops algorithms using neural networks for the segmentation and classification of aerial images.

 

Bálint JESZENŐI is a third-year student at Óbuda University in Computer Science Engineering, with a specialization in artificial intelligence. His areas of interest in his studies are software development, image processing, and machine learning. For his bachelor’s thesis, he is developing a model capable of monitoring endangered species through high-resolution aerial images.

Rebeka KISS earned her bachelor's degree in public administration, then an undivided master's degree in science of public governance (University of Public Service). She is currently a PhD student of the Doctoral School of Public Administration Sciences of the University of Public Service, also a law student at the Faculty of Law of Eötvös Loránd University (ELTE). Her main field of research is legislation. Within constitutional law, her research focuses on the explanatory memorandum of laws. She has been involved in the CAP and poltextLAB projects since 2019.

 

Anna TAKÁCS earned her bachelor's degree in Applied Economics from Corvinus University of Budapest. She is currently enrolled for the International Economy and Management master's programme at John von Neumann University, where her thesis focuses on the modelling of exchange rates using news articles. 

 

Viktor KOVÁCS is a 4th year Computer Science Engineer student at University of Szeged. His primary interests include machine learning, neural networks and natural language processing. He currently writes his bachelor's thesis on diagnostic classification of schizophrenia using state-of-the-art deep learning models.

Barbara BABOLCSAY earned her Bachelor’s degree in Mathematics from Eötvös Loránd University and is currently pursuing a Master’s degree in Applied Mathematics there, specializing in Stochastics. Her main interests are mathematical modelling as well as statistical (machine) learning and its explainability, which is also the topic of her thesis.

   

Developers

Richárd LEHOCZKI

 

Project Managers

Zoé BAUMGARTNER

Gergely JÁRAI

Kata ANCSIN

 

Krisztián IMRE earned his Business Communication degree at Budapest Metropolitan University. He is currently a final-year student at Budapest University of Technology and Economics, pursuing a master’s degree in Computational Cognitive Neuroscience with a supplementary Human-centered AI Masters program. Over the past decade, he has managed domestic and international IT research and development projects related to life sciences. His innovative work was recognized in 2018 with the “European Innovator of the Year” award in Brussels. As the project manager of poltextLAB, he supports the work of the IT team.