I am looking for partners in the research area.

I am looking for partners interested in the Horizon Europe Call.

I am looking for partners for the Horizon Europe research area.

I am looking for laboratory facilities in the research/application area.

PhD Student

Marcell Nagy

MSc

H-1111 Budapest, Műegyetem rkp. 3.

+3614635669

marcell.nagy94@edu.bme.hu

Groups

Human and Social Data Science Lab

Faculty

Institute of Mathematics

Department

Department of Stochastics

Research keywords: · data science · machine learning · network science · data visualization · educational data science · health data analytics
Horizon Europe keywords: · Artificial Intelligence and Robotics · Health technologies, new tools and solutions · Inclusive society · Next generation computing and data technologies

https://scholar.google.hu/citations?user=_Jocc8sAAAAJ&hl=en

https://www.linkedin.com/in/marcellnagy94/

https://twitter.com/MarcellNagy94

Publications Awards Projects Conferences

Publications

Molontay, R., & Nagy, M. (2022). How to improve the predictive validity of a composite admission score? A case study from Hungary. Assessment & Evaluation in Higher Education, 1-19.

Kui, B., Pintér, J., Molontay, R., Nagy, M., Farkas, N., Gede, N., ... & Hungarian Pancreatic Study Group. (2022). EASY‐APP: An artificial intelligence model and application for early and easy prediction of severity in acute pancreatitis. Clinical and Translational Medicine, 12(6), e842.

Nagy, M., & Molontay, R. (2022). Network classification-based structural analysis of real networks and their model-generated counterparts. Network Science, 1-24.

Kiss, S., Pintér, J., Molontay, R., Nagy, M., Farkas, N., Sipos, Z., ... & Szentesi, A. (2022). Early prediction of acute necrotizing pancreatitis by artificial intelligence: a prospective cohort-analysis of 2387 cases. Scientific Reports, 12(1), 1-11.

Nagy, M., & Molontay, R. (2021). Comprehensive analysis of the predictive validity of the university entrance score in Hungary. Assessment & Evaluation in Higher Education, 46(8), 1235-1253.

Kovács, P. T., Nagy, M., & Molontay, R. (2021). Comparative analysis of box-covering algorithms for fractal networks. Applied Network Science, 6(1), 1-37.

Molontay, R., & Nagy, M. (2021). Twenty years of network science: A bibliographic and co-authorship network analysis. In Big data and social media analytics (pp. 1-24). Springer, Cham.

Nagy, M., & Molontay, R. (2018, June). Predicting dropout in higher education based on secondary school performance. In 2018 IEEE 22nd international conference on intelligent engineering systems (INES) (pp. 000389-000394). IEEE.

Awards

Gyula Kőnig Young Researcher Award

Projects

HU-MATHS-IN, 2018-2021, research assistant, EFOP

Higher Education Institutional Excellence Program (FIKP), 2018-2021, Young researcher, NKFIH

Cooperative Doctoral Programme for Doctoral Scholarships, 2021-2023, researcher, NKFIH

HIVE HuBMAP Consortium, 2022, Fulbright Visiting Student Researcher, Fulbright Hungary, NIH Common Fund

Conferences

SITE 2022, San Diego USA, 2022 April, presenter

Networks 2021: A Joint Sunbelt and NetSci Conference, online, 2021 July, presenter

COMPLEX NETWORKS 2020, online, 2020 December, presenter

NetSci-X 2020, Tokyo Japan, 2020 January, poster presenter

11th ASONAM, Vancouver Canada, 2019 August, presenter

INES 2018, Las Palmas Spain, 2018 June,  presenter