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.

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.

Ádám KERÉNYI received his Ph.D. in Finance from the University of Szeged. He used to be an external reseracher at the Centre for Social Sciences, Institute for Political Science and a researcher at Institute of HUN-REN KRTK World Economics and at the Institute of International Economics and Business of the University of Szeged. His main research fields are the economic transition of the former socialist EU countries, public finance and financial stability.

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.

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. 

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.

Richárd LEHOCZKI

Zoé BAUMGARTNER

Enikő BARANYAI earned her bachelor’s degree in International Administration and is currently pursuing a Master’s degree in Community and Civil Development Studies at Eötvös Loránd University. She was previously engaged in professional roles within both the educational and civil society.