V-Shift Momentum Research Group
Our Team:
Principal Investigator:
Miklós SEBŐK is a Senior Research Fellow at the 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 currently serves as senior research fellow of the Institute for Political Science at the Centre for Social Sciences in Budapest. Miklós Sebők 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:
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).
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
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.
ádám kerényi
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.
Young Scholars:
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.
Viktor Kovács
Viktor KOVÁCS is a Computer Science Engineer graduated from the 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.
Anna Takács
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.
MARTIN BÁNÓCZY
Martin Balázs BÁNÓCZY is a third-year Computer Science Engineer student specializing in artificial intelligence at Óbuda 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
Barbara babolcsay
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.
Dávid László
Dávid LÁSZLÓ holds a BA in Philosophy, Politics and Economics from the University of York and an MSc in Economics from the London School of Economics (LSE). He previously worked as a predoctoral research fellow at LSE, focusing on environmental and development economics. His main interests lie in statistical machine learning and its applications to development policy.
Developers:
Richárd Lehoczki
LÁSZLÓ MARCELL KISS
László Marcell KISS obtained his M.Sc. degree specializing in Economic Mathematics at Corvinus University of Budapest. He was awarded the Pro Scientia Award in Economics for his research achievements. His master’s thesis analyzed the role of verbal and non-verbal sentiment in FOMC press conferences and their effects on asset prices.
dávid tokovics
Dávid TOKOVICS earned a BSc degree in Computer Science Engineering from the Budapest University of Technology and Economics, and subsequently worked in risk management sector. His main areas of interest are Hungarian politics, social psychology, and statistical analyses conducted in these fields.
Project Managers:
Zoé Baumgartner
Enikő Baranyai
Contributors in earlier phases
Ákos Holányi
Norbert Huszti
Sándor Kozák
Dorottya Lovász
Melinda Manczinger
Ákos Máté
Levente Pakot
Laura Seben
Áron Somogyi
Ágnes Tőrös