Viera Rozinajová

Research areas: data analytics, predictive modeling, optimization, anomaly detection, energy domain

Position: Expert Researcher

Viera is a senior researcher focusing on intelligent data analysis, particularly predictive modeling, cluster analysis, anomaly detection and optimization. She has been active in the artificial intelligence area for a long time. Before her employment at KInIT, she worked as an associate professor at the Faculty of Informatics and Information Technologies at the Slovak University of Technology in Bratislava (FIIT STU), where she headed up the Big Data Analysis group. She has authored/co-authored more than 70 publications in scientific journals and conferences. She has participated in more than 25 national and international research projects and has led several of them. She regularly reviews submissions to scientific journals (Springer, Elsevier, IEEE) and international conferences.

She worked for 4 years as a research fellow at the University of Stuttgart and from 2011 to 2019 was a vice-dean of FIIT STU responsible for research, projects and industry co-operation.
She is a member of IFIP TC8 (Information Systems) as a national representative of Slovakia, vice-chairman of the Scientific Board of the Slovak Research Centre for Artificial Intelligence and a member of ACM and the Slovak Computer Science Society.

Selected activities

  • member of IFIP TC8 (Information Systems) as a national representative of Slovakia,
  • vice-chairman of the Scientific Board of the Slovak Research Centre for Artificial Intelligence

Activities in the past:

  • research fellow at the University Stuttgart
  • vice-dean responsible for research, projects and industrial cooperation at FIIT STU
  • guarantor of the PhD study at FIIT STU
  • member of the Scientific Board of FIIT STU
  • reviewer of dissertation (9) and habilitation (4) theses
  • member of executive committee of Slovak Computer Society

Professional Service

Reviews in journals:

  • Future Generation Computer Systems (Elsevier),
  • Biocybernetics and Biomedical Engineering (Elsevier),
  • International Journal of Electrical Power and Energy Systems (Elsevier),
  • Evolutionary Intelligence (Springer),
  • Vietnam Journal of Computer Science (World Scientific),
  • Entropy (MDPI)

Projects:
Grant agencies: Japan Science and Technology Agency, SASPRO2, APVV, VEGA, KEGA, GAČR

Conferences:
Member of PC: ECIS, DEXA, ADBIS, DISA, NWESP, SAMI

Professional organizations:
Member of ACM, IFIP, Slovak Research Centre for Artficial Intelligence Research, Slovak Computer Society

Other notable projects

Knowledge-Based Approaches for Intelligent Analysis of Big Data

APVV-16-0213. 2017-2021. Partner: Technical University of Kosice (prof. Jan Paralic), Rozinajova, V. – principal investigator for FIIT STU until August 2020

NEWTON – Networked Labs for Training in Sciences and Technologies for Information and Communication

H2020 688503. 2016-2019. Coordinator: Dublin City University, Rozinajova, V. – principal investigator for FIIT STU

International Centre of Excellence for Research of Intelligent and Secure Information-Communication Technologies and Systems

ITMS 26240120039. 2014-2015. Partner: Atos IT Solutions and Services s.r.o., Rozinajova, V. – principal investigator for FIIT STU

International Centre of Excellence for Research of Intelligent and Secure Information-Communication Technologies and Systems – II. Stage

ITMS 313021W404. Partner: Atos IT Solutions and Services s.r.o. , Rozinajova, V. – principal investigator for FIIT STU until August 2020

STU as the Leader of Digital Coalition

002STU-2-1/2018. 2019. Rozinajova, V. – principal investigator for FIIT STU

Selected Student Supervising

She supervised more than 80 bachelor, master and PhD theses. Selected student theses:

PhD

  • Miroslav Blšták: Automatic Question Generation Based on Sentence Structure Analysis (defended in 2018)
  • Roman Šelméci: Application of Design Patterns in Service Oriented Architecture (defended in 2018)
  • Petra Vrablecová: Predictive Analytics on Data Streams (defended in 2019)
  • Marek Lóderer: Application of Biologically Inspired Algorithms in Prediction Based on Ensemble Learning
  • Matej Kloska: Advanced Methods of Anomaly Detection
  • Jaroslav Loebl: Genetic Programming in Data Clustering
  • Miriama Pomffyová: Multi-objective optimization methods

Master

  • Adrián Kubica: Microgrid optimization (ongoing)
  • Michal Halás: Management of energy sharing in micronetworks (ongoing)
  • Alan Kováč: Optimization of microgrid operation using data analytics methods (ongoing)
  • Michal Staškovan: Methods of feature selection in research of oncology diseases (defended in 2019)
  • Martina Halajová: Relevant feature selection in the research of cancer treatment (defended in 2019)
  • Richard Pinter: Predictive analysis and its utilization on intelligent house (defended in 2019)
  • Martin Prekala: Optimization of energy production and consumption (defended in 2018)
  • Miriama Pomffyová: Intelligent data analysis in power load environment (defended in 2018)
  • Martin Žalondek: Utilization of data analytics in regulation of consumption and production of electric energy (defended in 2017)
  • Helmut Posch: Modelling of energy ecosystem (defended in 2017)
  • Radoslav Nemec: Prediction of power load demand (defended in 2016)
  • Andrej Piliar: Prediction of energy produstion (defended in 2016)
  • Eduard Kubinec: Utlization of business analytics for making enterprise processes more effective (defended in 2016)
  • Andrej Štajer: Visual analytics of large volume data (defended in 2015)
  • Ivan Martoš: Software services recommendation considering context (defended in 2015)

Bachelor

  • Samuel Sagan: Analysis and Visualization of data in Energy Domain (defended in 2020)
  • Šimon Mišenčík: Analysis and Visualization of data in Energy Domain (defended in 2020)
  • Kamil Džurman: Tool for comparison of optimization algorithms (defended in 2019)
  • Michal Halás: Application for drivers of electric cars (defended in 2019)
  • Adrián Kubica: Application for drivers of electric cars (defended in 2019)
  • Peter Pavlík: Dynamic Weighted Majority in Ensemble Learning (defended in 2018)
  • Ján Marián Franko: Effective utilization of energy in local energy network (defended
  • In 2018)
  • Michal Dolnák: Processing the data from intelligent metering devices (defended in 2017)
  • Martin Škodáček: Processing the data from intelligent metering devices (defended in 2017)
  • Michal Staškovan: Application supporting enery savings in household (defended in 2017)
  • Dominik Kačmár: Application supporting enery savings in household (defended in 2017)
  • Simon Sudora: Prediction of energy production from renewable sources involving external factors (defended in 2016)
  • Oliver Moravčík: Prediction of energy production from renewable sources involving external factors (defended in 2016)
  • Peter Bakoš: Monitoring energy demand in households (defended in 2016)
  • Miriama Pomffyová:Utilization of power load demand predictions in energy purchase planning (defended in 2016)
  • Martin Lačný: Enterprise architecture as a means of making processes in organization more effective (defended in 2015)
  • Tomáš Gaššo: Enterprise architecture as a means of making processes in organization more effective (defended in 2015)
  • Gabriel Takács: Personal recommendation using machine learning techniques (defended in 2015)