WHO I AM

I'M MIHA MLAKAR

A RESEARCHER

MIHA MLAKAR

RESEARCHER

Hello There!

My life is intertwined with two passions. One is tennis and the other is science. I am lucky enough to have an opportunity to be successful in both.
Nevertheless, I have a feeling that my career as a researcher has only just began. I look forward to goals I want to achieve and things I want to discover.

Currently I work as a postdoctoral associate at Department of Intelligent Systems (DIS) at Jozef Stefan Institute. My research is focused on the field of sport science, more precisely on extracting applicable knowledge from large amounts of data.

Welcome to my page, welcome to my life.


Birthdate : 19/09/1984
Skype : mmhihec
Phone : +386 1 477 3633
Email : miha.mlakar@ijs.si
Address : Jamova cesta 39, 1000 Ljubljana, Slovenia.
Publications : Cobiss

Education

  • 01
    Jo┼żef Stefan International Postgraduate School

    Ljubljana, Slovenia

    Ph.D. Thesis: Evolutionary multiobjective optimization based on Gaussian process modeling

    2010-2015

  • 02
    Faculty of Economics

    Ljubljana, Slovenia

    Master thesis in progress.

    2010-2016

  • 03
    Faculty of Computer and Information Science

    University of Ljubljana, Slovenia

    Graduated from Computer and Information Sciences

    2003-2010

Research

  •  
    Research on government spending

    I analysed various databases like public procurement database, Slovenian business register, database of municipalities. I looked for cash flow trends and connections between municipalities and companies. I tried to predict which company will get a specific public

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  •  
    Computer support for the reassembly of wall-painting fragments

    In collaboration with the Restoration Centre in Ljubljana we (DIS) developed a mobile and web application e-Pedius for the computer based support for the reassembly of wall-painting fragments. The solution supports crowd-sourcing and is accessible to wider

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  •  
    The GP-DEMO algorithm

    For my PhD. thesis I developed a new algorithm called GP-DEMO. The algorithm proved to be very efficient in solving computationally complex multi-objective optimization problems. It is based on evolutionary algorithms and uses Gaussian process modelling within

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  •  
    Optimization of the continuous steel casting process

    In collaboration with steel company Store Steel we (DIS) developed a web application called VizEMO-Steel that supports optimization of the continuous steel casting process and visualization of the results. The optimization process is done with the use

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