Petra Vrablecová

Research areas: data mining, artificial intelligence, time series analysis, forecasting

Position: Researcher 10/2020-06/2023

Petra focuses on data mining, intelligent data analysis methods and high-volume data processing. She is especially interested in stream processing, stream mining and time series analysis, applying these approaches to improve forecasting of energy production and consumption, as well as to co-opt intelligent data analysis methods to support green energy solutions.

She has been involved in several research projects and co-operated with industrial partners in this area, including Atos and sféra. She has published at both local and international conferences related to data mining, information systems and information processing. Prior to accepting her current position at KInIT, she was a researcher at the Slovak University of Technology in Bratislava, where she successfully completed her PhD in intelligent information systems.

Other notable projects

Knowledge-Based Approaches for Intelligent Analysis of Big Data

feb 24. 2021
APVV-16-0213. 2017-2021. Partner: Technical University of Kosice (prof. Jan Paralic), Rozinajova, V. – principal investigator for FIIT STU until August 2020

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

feb 24. 2021
ITMS 313021W404. Partner: Atos IT Solutions and Services s.r.o. , Rozinajova, V. – principal investigator for FIIT STU until August 2020

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

feb 24. 2021
ITMS 26240120039. 2014-2015. Partner: Atos IT Solutions and Services s.r.o., Rozinajova, V. – principal investigator for FIIT STU

Better Utilization of Green Energy through Better Modelling

feb 24. 2021
BFN16-ENV-010. 2017-2018, Partners: University of Bergen (prof. Tor Sørevik), Lucka, M. – principal investigator

Selected Student Supervising

Master

  • Maruškin Erik – Completion of time series properties in data streams. Defended 2021
  • Nagyová Kitti – Impact analysis of applying new components into microgrids. Defended 2020
  • Škodáček Martin – Data stream anomaly detection. Defended 2019
  • Fukas Martin – Detection of outliers in time series data. Defended 2019

Bachelor

  • Polkorábová Diana – Microgrid simulation. Defended 2020
  • Hoferica Andrej – Utilization of electric vehicles as a power storage system. Defended 2020
  • Otruba Marek – Simulation of usage large-capacity battery in smart home network. Defended 2018
  • Procházka Matej – Simulated usage of high-capacity battery in household smart grid. Defended 2018