Mária Lucká

Research areas: optimization, microgrid modeling, bioinformatics, algorithms

Position: Researcher

Mária is a professor of applied informatics whose research has focused on high-performance computing and on developing effective algorithms for various parallel architectures. In addition, she has studied whether artificial intelligence methods could be applied to process large data volumes in finance, biology and medicine. At present, she uses her experience in modeling and optimization to solve problems in the smart grid and microgrid environments.

She participated in projects at the University of Vienna and in international projects, where she collaborated with the University of Bergen.

As a teacher, she has supervised 50 Bachelor’s, 63 Master’s and three PhD students. She is an author or co-author of more than 60 papers with more than 400 citations.

She is a reviewer for several international journals in Springer, IEEE and ACM, as well as in the Slovak granting agencies VEGA and KEGA. She is also a member of ACM and the Slovak IT Society.

Selected activities

  • member of the specialization committee of doctoral studies at FIIT STU in Bratislava, in the field of 9.2.9 Applied Informatics
  • member of the specialization committee of doctoral studies at Faculty of Management Science and Informatics, University Žilina in Žilina, in the field of 9.2.9 Applied Informatics
  • supervisor of doctoral studies at Faculty of Management Science and Informatics, University Žilina in Žilina, in the field of 9.2.9 Applied Informatics
  • supervisor of doctoral studies at FMFI UK in Bratislava, in the field of 9.2.9 Applied Informatics

Professional Service

  • Reviewer of research grant agencies VEGA and KEGA
  • Reviewer for IEEE, Springer, ACM
  • Program committee member:
  • Member of the Slovak Commission for the Olympiad in Informatics in the years 2010-2013
  • Member of the Slovak Commission for the Mathematical Olympiad in the years 2002-2013

Other notable projects

Errors and Uncertainties in DNA Sequencing: Algorithms and Models

feb 24. 2021
VEGA 1/0458/18. 2018-2021, Partners: Comenius University in Bratislava (assoc. prof. Tomáš Vinař), Lucka, M. – principal investigator

Tumor Heterogeneity in Multiple Myeloma: Evolution and Clinical Significance

feb 24. 2021
APVV-16-0484. 2017-2021, Lucka, M. – principal investigator at 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

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

Intelligent Analysis of Big Data by Semantic-Oriented and Bio-Inspired Methods in a Parallel Environment

feb 24. 2021
VEGA 1/0752/14. 2014-2017, Navrat, P. – principal investigator

Do You Know, What You Know?

feb 24. 2021
KEGA 175-006 TVU-4/2010. 2010–2011. Lucka, M. – principal investigator

Student Supervising


  • Jarábek Tomáš – Application of Deep Learning Methods on Processing of Biomedical Data. Ongoing
  • Laurinec Peter – Improving Forecasting Accuracy Through the Influence of Time Series Representations and Clustering. Defended 2018. — Senior Data Scientist at PowereX
  • Piecka Stanislav – Parallel Ant Colony Optimization Method for Solving Vehicle Routing Problem. Defended 2012. — CEO at TransData s.r.o.

Masters (since 2014)

  • Bedejová Katarína – Informatic means for gene expression analysis. Defended 2020
  • Vašš Maroš – Prediction and optimization in the microgrid. Defended 2020
  • Kamenský Jozef – Modeling in the Smart Grid Environment. Defended 2020
  • Žilka Dominik – Optimization of layout of electromobiles charging stations. Defended 2019
  • Sitarčík Jozef – DNA sequence mapping. Defended 2018
  • Nemček Martin – Density based downsampling of cytometry data and clinical outcome prediction using clinical data. Defended 2018
  • Moravčík Oliver – Clustering analysis of cytometry data for purpose of cell population identification. Defended 2018
  • Kovalenko Maryna – Electricity price forecasting in Smart Grids. Defended 2018
  • Bendík Jakub – Modeling in an environment of intelligent networks. Defended 2018
  • Valíček Šimon – Parallel methods of mapping DNA sequences. Defended 2017
  • Osvald Vladimír – Using stream data processing methods to create an adaptive prediction model for power consumption. Defended 2017
  • Kopšo Roman – Security Based Clustering and Analysis of Big Log Files. Defended 2017
  • Katkó Daniel – Parallel indexing and error recovery of short DNA sequences. Defended 2016
  • Horváth Peter – Predictions of time series using neural networks in big data environments. Defended 2016
  • Farkaš Tomáš – Deep analysis and clustering of big data files. Defended 2017
  • Csóka Lukáš – Parallel clustering of large data files. Defended 2017
  • Blanárik Filip – Methods of lossless compression of DNA sequences. Defended 2016
  • Jamečná Eva – Multiple sequence alignment by the ant colony algorithm. Defended 2016
  • Horváth Peter – Time series prediction using neural networks in Big Data. Defended 2016
  • Soós Daniel – Stochastic optimization algorithm solution for restriction mapping of DNA fragments. Defended 2015
  • Daráž Jakub – Parallel models for solving large optimization problems using ant colony. Defended 2015
  • Kucsera Viktor – Parallel Methods of Image Segmentation by Using Ant Colony Optimization.  Defended 2014
  • Kollár Adrián – Document clustering optimization. Defended 2014

Bachelors (since 2014)

  • Bazger Martin – Methods for finding the similarity of large sequences. Defended 2020
  • Balaj Kristián – Analysis and comparison of biological sequences by methods without alignment. Defended 2020
  • Pomichal Vajk – Visualization of the cytometric data analysis results. Defended 2019
  • Gáfrik Andrej – Improvement and parallelization of the ant colony optimization algorithm. Defended 2019
  • Balga Miroslav – Search for changes in the genetic code using biologically inspired algorithms. Defended 2019
  • Zeliska Michal – Search for changes in the genetic code using biologically inspired algorithms. Defended 2019
  • Revay Marcus – Interactive support for teaching subject AZA. Defended 2018
  • Činčurak Martin – Informatic support for the processing of big data files in biomedicine. Defended 2018
  • Popelka Ľudovít – Informatics support for large datasets processing in biomedicine. Defended 2018
  • Vašš Maroš – Automated pre-processing of large cytometric data. Defended 2018
  • Mičo Jakub – Parallel methods of pattern recognition in big data. Defended 2017
  • Mazúr Slavomír – Parallel methods of searching for patterns in large data files. Defended 2017
  • Urminský Milan – Prediction of electricity consumption using methods of swarm intelligence. Defended 2016
  • Sitarčík Jozef – Approximate string matching in large data bases. Defended 2016
  • Javorník Dušan – Prediction of electricity consumption using neural networks in the environment of increasing data. Defended 2016
  • Farkaš Tomáš – Parallel data sorting. Defended 2015
  • Csóka Lukáš – Parallel methods for clustering large data corpora. Defended 2015
  • Vrba Benjamín Jakub – Parallel image classification with use of Random Forests method. Defended 2015
  • Roba Roman – Processing of large graphs with application to financial flows of cryptocurrencies and analysis of blockchains. Defended 2015
  • Daabousová Ranja – Prediction models of electricity consumption by intelligent analysis of large corpus of data. Defended 2015
  • Kuric Dejan – Visualisation of graph algorithms. Defended 2014
  • Katkó Daniel – Visualization of graph algorithms. Defended 2014
  • Uderman Daniel – MPI parallel implementation of the supply problem with use of ACO. Defended 2014