Hermina Petric Maretić, Software Developer in Zagreb, Croatia
Hermina Petric Maretić

Software Developer in Zagreb, Croatia

Member since August 27, 2014
Hermina is a developer with proven skills in data mining, machine learning, and mathematical optimization. When building a project, she gives special attention to algorithm efficiency, putting an emphasis on creating quick and optimized software.
Hermina is now available for hire




Zagreb, Croatia



Preferred Environment

MATLAB, C++, Django, Python, Windows, Linux

The most amazing...

...thing I've coded is a hybrid of an ants algorithm for optimization. It achieves results in seconds that take other heuristic algorithms days to reach.


  • Competitor

    2014 - 2014
    Mozgalo Competition
    • Created a web scraper that gathered millions of sentences describing beers, using PHP.
    • Determined which aspect of beer a sentence is discussing, using SVD in Python.
    • Graded sentences with machine learning algorithms and determined the final grade for every beer.
    • Developed a web application to present an extensive analysis of results using Bootstrap, HTML, JavaScript, Python, and Django.
    • Built a recommender system using Python.
    Technologies: Bootstrap, JavaScript, PHP, MySQL, Django, Python
  • Student

    2009 - 2014
    University of Zagreb
    • Developed face recognition software using Singular Value Decomposition (SVD) in MATLAB.
    • Created text classification software thoroughly analyzed approaches using Python.
    • Built a student web page using PHP, JavaScript, MySQL, CodeIgniter, and HTML.
    • Created a metaheuristical approach to the Hamiltonian completion problem using MATLAB.
    • Implemented an algorithm for finding closest points. Used an object-oriented paradigm, implemented data structures, and competed in algorithm competitions using C++.
    • Performed statistical analysis of data in R and SAS.
    Technologies: C#, SAS, R, HTML, JavaScript, SQL, PHP, MATLAB, Python, C++, C
  • Researcher (Intern)

    2013 - 2013
    EPFL (Ecole polytechnique fédérale de Lausanne)
    • Conducted research in Bioinformatics and Computational Biology.
    • Implemented an algorithm for finding the shortest path in a graph using a specific set of biology-conditioned rules.
    • Worked on an iterative algorithm to improve evolutionary trajectories.
    • Showed that a simplified model with only DCJ (double-cut-and-join) operations wouldn't work if transposition, deletion, and duplication operations were added.
    • Worked on a modification of the model allowing it to handle all of the above-mentioned operations.
    Technologies: Linux
  • Developer (Intern)

    2012 - 2012
    Ericsson Nikola Tesla
    • Redirected calls using Java.
    • Created a scalable database for users.
    • Created a dynamic web page using Bootstrap.
    • Tested the page in a real-life active telecommunication network.
    • Showed user location using Google Maps.
    Technologies: JavaScript, Bootstrap, Google Maps API, Java


  • Mozgalo

    A data mining project for finding the best beer. Information is gathered from web pages, stored in a database, and analyzed using numerous machine learning methods. The application is realized as a dynamic web page with numerous analysis options: best beer by category, by city, popularity over time, and more. In addition, a recommender system was created with the possibility of grading a user's own comments, as well as options to renew the data and explore the database. The project was realized in Python, Django, PHP, and JavaScript.

  • Text classification by subjectivity

    It classifies text using a naive Bayes classificator and support vector machine classificator. It provides extensive analysis on best feature selection and achieves very good results (92% accuracy). Technologies used: Python, NLTK, SciPy, and NumPy.

  • Student website

    A simple website for students. Carefully chosen features combine everything a student needs. It was realized in PHP, CodeIgniter, Bootstrap, and JavaScript.

  • Metaheuristics

    A metaheuristical approach to the Hamiltonian completion problem. It features genetic algorithms, an Ants algorithm, an immunological algorithm, and a hybrid of an Ants algorithm, which gave the best results by far. It also features extensive analysis of the solution approaches, and was implemented in MATLAB.


  • Languages

    Python, C++, C, SQL, PHP, R, JavaScript, C#, SAS, Java, HTML
  • Tools

  • Paradigms

    Object-oriented Design (OOD), Object-oriented Programming (OOP), Test-driven Development (TDD)
  • Platforms

    Linux, Windows
  • Other

    Machine Learning
  • Frameworks

    Bootstrap, Django, .NET
  • Libraries/APIs

    SciPy, NumPy, Google Maps API, Matplotlib
  • Storage

    MySQL, PostgreSQL


  • Master's Degree in Mathematical Statistics
    2013 - 2015
    University of Zagreb - Zagreb, Croatia
  • Master's Degree in Computer Science
    2012 - 2014
    University of Zagreb - Zagreb, Croatia
  • Bachelor's Degree in Mathematics
    2009 - 2012
    University of Zagreb - Zagreb, Croatia

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