Ágnes Fogarassyné Vathy - ODT Personal data sheet


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Personal data sheet

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personal data approved: 2023. XII. 03.

Personal data

name	Ágnes Fogarassyné Vathy
name of institution	University of Pannonia
doctoral school	PE Doctoral School of Information Science and Technology (Supervisor Az oktató valamelyik doktori iskolában egy vagy több doktorandusz vagy doktorjelölt munkáját irányítja. )
the share of work in the different doctoral schools.	PE Doctoral School of Information Science and Technology 100%

Contact details
E-mail address	vathydcs.uni-pannon.hu
phone number	+36 88 624-712
	own web page

Academic title
scientific degree, title	Ph.D.
year degree was obtained	2009
discipline to which degree belongs	computer sciences
institution granting the degree	Eötvös Lóránd University

Employment
1998 -	University of Pannonia university professor or researcher

Thesis topic supervisor

number of doctoral students supervised until now

number of students who fulfilled course requirements

1.5

students who obtained their degrees:

(50%)

Dániel Leitold

PhD

2020

DSIST-PE

students with degree granting in process:

Szabolcs Szekér

PhD

(2024/01)

DSIST-PE

present PhD students:

	Veronika Eszter Gombás	(PhD)	(2027/08)	DSIST-PE
(50%)	Tamás Miseta	(PhD)	(2026/01)	DSIST-PE
(50%)	Attila Knolmajer	(PhD)	(2025/08)	DSIST-PE
(50%)	Gábor Arányi	(PhD)	(2025/08)	DSIST-PE
	János Kontos	(PhD)	(2024/08)	DSIST-PE

hiányos adatú hallgatói:

Szabolcs Szekér

PhD

()

DSIST-PE

Thesis topic proposals

Research
research area	data mining, data mining technologies in healthcare, machine learning, predictive analytics
research field in which current research is conducted	computer sciences

Publications

2022

Vathy-Fogarassy Ágnes, Vassányi István, Kósa István: Multi-level process mining methodology for exploring disease-specific care processes, JOURNAL OF BIOMEDICAL INFORMATICS 125: p. 103979.
type of document: Journal paper/Article
number of independent citations: 3
language: English
URL

2022

Miseta Tamás, Fodor Attila, Vathy-Fogarassy Ágnes: Energy trading strategy for storage-based renewable power plants, ENERGY 250: p. 123788.
type of document: Journal paper/Article
number of independent citations: 2
language: English
URL

2020

Szekér Szabolcs, Vathy-Fogarassy Ágnes: Weighted nearest neighbours-based control group selection method for observational studies, PLOS ONE 15: (7) e0236531
type of document: Journal paper/Article
number of independent citations: 5
language: English
URL

2019

Leitold Daniel, Vathy-Fogarassy Agnes, Abonyi Janos: Evaluation of the Complexity, Controllability and Observability of Heat Exchanger Networks Based on Structural Analysis of Network Representations, ENERGIES 12: (3) pp. 1-24.
type of document: Journal paper/Article
number of independent citations: 13
language: English
URL

2019

Fogarassy György, Vathy-Fogarassy Ágnes, Kenessey István, Kásler Miklós, Forster Tamás: Risk prediction model for long-term heart failure incidence after epirubicin chemotherapy for breast cancer–A real-world data-based, nationwide classification analysis, INTERNATIONAL JOURNAL OF CARDIOLOGY 285: pp. 47-52.
type of document: Journal paper/Article
number of independent citations: 16
language: English
URL

2017

Dániel Leitold, Ágnes Vathy-Fogarassy, János Abonyi: Controllability and observability in complex networks – the effect of connection types, SCIENTIFIC REPORTS 7: 151
type of document: Journal paper/Article
number of independent citations: 43
language: English
URL

2017

Vathy-Fogarassy Ágnes, Hugyák Tamás: Uniform data access platform for SQL and NoSQL database systems, INFORMATION SYSTEMS 69: pp. 93-105.
type of document: Journal paper/Article
number of independent citations: 57
language: English
URL

2017

Krisztina Tóth, Károly Machalik, György Fogarassy, Ágnes Vathy-Fogarassy: Applicability of Process Mining in the Exploration of Healthcare Sequences, In: Szakál, Anikó (szerk.) 2017 IEEE 30TH NEUMANN COLLOQUIUM (NC), Óbudai Egyetem (2017) pp. 151-155.
type of document: Part of book/Proceedings Paper
number of independent citations: 12
language: English
URL

2013

Ágnes Vathy-Fogarassy, János Abonyi: Graph-Based Clustering and Data Visualization Algorithms, Springer-Verlag Wien
type of document: Book/Monography
number of independent citations: 49
language: English
URL

2006

Vathy-Fogarassy A, Kiss A, Abonyi J: Hybrid minimal spanning tree and mixture of gaussians based clustering algorithm, LECTURE NOTES IN COMPUTER SCIENCE 3861: pp. 313-330.
type of document: Journal paper/Article
number of independent citations: 40
language: English
URL

Number of independent citations to these publications:

240

Scientometric data

list of publications and citations

number of scientific publications that meet accreditation criteria:

113

number of scientific publications:

113

monographs and professional books:

monographs/books in which chapters/sections were contributed:

scientific publications published abroad that meet the accreditation criteria:

publications not in Hungarian, published in Hungary, meeting the accreditation criteria:

number of independent citations to scientific publications and creative works:

530

2024. IV. 17.
ODT ülés
Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).