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Prof. Dr. Olga Kurasovaolga kurasova

Department: Cognitive Computing Group

Position: Principal Researcher, Professor


Address: Akademijos st. 4, room 620, Vilnius
Tel: (+370 5) 210 9322
E-mail:  

Social profiles:

 

Scientific and Pedagogical Background

Ph.D. in Computer Science, Associate Professor

Research Work

Scientific interests include

  • Data Mining,
  • Multidimensional Data Visualization,
  • Big Data analysis,
  • Artificial Neural Networks,
  • Machine Learning,
  • Optimization Methods,
  • Multi-objective Optimization,
  • Evolutionary Computing,
  • Image Processing.

Scientific publications

Publications with VU Institute of Data Science and Digital Technologies & Institute of Mathematics and Informatics affiliation

Scientific and other projects

COST actions:

  • BIG-SKY-EARTH: Big Data Era in Sky and Earth Observation (COST TD1403), 2014-2018.
  • cHiPSet: High-Performance Modelling and Simulation for Big Data Applications (COST IC1406), 2015-2019.
  • SoftStat: Combining Soft Computing Techniques and Statistical Methods to Improve Data Analysis Solutions (COST IC0702), 2009-2012.

 

National and international projects:

  • EuroStars project: PEN – Production Effectiveness Navigator, EuroStars project E!6232, 2011-2014.
  • Theoretical and Engineering Aspects of E-Service Technology Development and Application in High-Performance Computing Platforms, 2012-2015.
  • Development of Data Analysis Methods and Tools (2013-02-12 Agreement between "Informatikos mokslų centras" and Vilnius University).
  • Innovation voucher No. 31V-109 (JSC "Algoritmų sistemos", MITA): Analysis of optimization strategies, implementation possibilities and methods of Artificial Neural Networks for complex decisions, 2012.
  • Comparative quantitative and qualitative research "Estimation of demand of engineering studies specialists in Lithuania, Estonia and Poland". Agreement with Vilniaus kolegija (University of Applied Sciences).
  • Development of the prototype for interaction between the network of sensors and local component of information collecting, transferring and representation. Agreement with JSC "Diagnostinės sistemos." No. 12-17.01/2010.
  • Representing of critical physiological parameters data, and development of a decision making algorithm and decision making subsystem prototype [sub-project of "Creation of an efficient system for constant observation of critical physiological parameters", 2010-12-08 – 2010-12-31.
  • Human genome diversity determined pathogenetic mechanisms of atherosclerosis (ATHEROGEN), 2004-2006.
  • Information technologies for human health - support of clinical decisions (e-health). Acronym "IT Health", 2003-2006.
  • Development program of the technology project "Information technology tools of clinical decision support and citizens' wellness for the e- Health system (Info Health)", 2007-2009.

Presentations at Scientific Conferences

  • Massive Data Visualization via Selecting a Data Subset. 8th international workshop on data analysis methods for software systems, Druskininkai, Lithuania, December 1-3, 2016.
  • Classification-Based Storage of JPEG Images. 8th international workshop on data analysis methods for software systems, Druskininkai, Lithuania, December 1-3, 2016.
  • Multi-Level Method for Big Data Visualization. 8th international workshop on data analysis methods for software systems, Druskininkai, Lithuania, December 1-3, 2016.
  • Artificial Neural Networks for Massive Data Visualization. EURO 2016: 28th European Conference on Operational Research, Poznan University of Technology, Poznań, Poland, July 3-6, 2016.
  • Decision Tree Classification to Predict Effect of JPEG Compression on Images. EURO 2016. 28th European Conference on Operational Research, Poznan University of Technology, Poznań, Poland, July 3-6, 2016.
  • Visual Analytics for Big Data. 7th international workshop on data analysis methods for software systems, Druskininkai, Lithuania, December 3-5, 2015.
  • Image Classification for Quality Prediction after JPEG Compression. 7th international workshop on data analysis methods for software systems, Druskininkai, Lithuania, December 3-5, 2015.
  • Extensions of the Preference-based Multi-objective Evolutionary Algorithm R-NSGA-II. 5th international workshop on data analysis methods for software systems, Druskininkai, Lithuania, December 4-6, 2014.
  • A review of Data Mining Systems Based on Web Services. 5th international workshop on data analysis methods for software systems, Druskininkai, Lithuania, December 5-7, 2013.
  • Web Service-based Data Mining Systems. 26th European Conference on Operational Research, 1-4 July, 2013, Rome, Italy.
  • Integrated Visualization of Vector Quantization by Multidimensional Scaling. Workshop on Computer Graphics, Vision and Mathematics (GraVisMa 2009), September 2-4, 2009, Plzen, Czech Republic.
  • Visualization of Support Vectors. XIII International Conference on Applied Stochastic Models and Data Analysis (ASMDA-2009), June 30- July 3, 2009, Vilnius, Lithuania.
  • Combination of Vector Quantization and Visualization. 6th International Conference on Machine Learning and Data Mining, MLDM 2009, July 23-25, Leipzig, Germany.
  • Rule Induction for Ophthalmological Data Classification, EURO Mini Conference on Continuous Optimization and Knowledge-Based Technologies, May 20-23, 2008, Neringa, Lithuania.
  • Parameter System for Human Physiological Data Representation and Analysis, 3rd Iberian Conference on Pattern Recognition and Image Analysis, June 6-8, 2007, Girona, Spain.

Ph.D. Supervision and Lecturing

Supervisor of five Ph.D. students, who have defended successfully their Ph.D. theses:

  • Alma Molytė "Investigation of Combinations of Vector Quantization Methods with Multidimensional Scaling". 2011-06-29.
  • Ernestas Filatovas "Solving Multiple Criteria Optimization Problems in an Interactive Way". 2012-03-28.
  • Gintaras Vaira "Genetic Algorithm for Vehicle Routing Problem". 2014-06-10.
  • Pavel Stefanovič "Visualization of Self-Organizing Maps and Estimation of Their Quality". 2015-06-30.
  • Olegas Niakšu "Development and Application of Data Mining Methods in Medical Diagnostics and Healthcare Management". 2015-09-21.

 

PhD Supervision

Leads PhD Students:

   

Teaching subjects (Bachelor and Master studies):

  • Artificial Intelligence
  • Computational Intelligence and Decision Making
  • Artificial Neural Networks

Membership of editorial boards

 

Membership of scientific societies