Biography

Grega Vrbančič is an Assistant Professor and a member of the Institute of Informatics at the University of Maribor, Faculty of Electrical Engineering and Computer Science. His primary research interests include Artificial Intelligence and Machine Learning - especially the area of Deep Learning.

Interests
  • Artificial Intelligence
  • Machine Learning
  • Deep Learning
  • Data Science
Education

  • PhD in Computer Science, 2021

    University of Maribor, Faculty of Electrical Engineering and Computer Science

  • MSc in Information Technology, 2017

    University of Maribor, Faculty of Electrical Engineering and Computer Science

  • BSc in Information Technology, 2015

    University of Maribor, Faculty of Electrical Engineering and Computer Science

Publications

Uporaba programskega jezika Julia za namene podatkovne znanosti
Programski jezik Julia je v zadnjih letih pridobil veliko pozornosti zaradi svoje edinstvene kombinacije zmožnosti programiranja na …
Tadej Lahovnik, Grega Vrbančič, Vili Podgorelec
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Profiling the Arion rufus snails with computer vision
Smart agriculture takes advantage of modern computational approaches that vary from IoT, cloud computing, and artificial intelligence. …
Grega Vrbančič, Rok Kukovec, Vili Podgorelec, Sancho Salcedo-Sanz, Iztok Jr. Fister
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Digital Transformation Using Artificial Intelligence and Machine Learning: An Electrical Energy Consumption Case
Companies nowadays eagerly compete in providing their customers with the best possible services, where the companies in the electrical …
Vili Podgorelec, Sašo Karaktič, Iztok Jr. Fister, Lucija Brezočnik, Špela Pečnik, Grega Vrbančič
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My writtings

Keras with Tensorflow - How to flush CUDA Memory
As a young researcher working in the field of machine learning, I am on a regular basis utilizing GPUs to train different kinds of neural networks such as convolutional neural networks to tackle various problems.
Grega Vrbančič
May 10, 2020 3 min read Tips
FastAPI and Celery
In this post, I will present to you a simple, minimal working example of utilizing new, high-performance Python web framework FastAPI and Celery - Distributed Task Queue for executing long-running jobs.
Grega Vrbančič
Last updated on Jul 4, 2019 5 min read Guides
How to utilize NiaPy for solving KNN parameter optimization problem?
In the following, I’m going to present to you, an example on how to utilize NiaPy micro-framework 1 for solving the parameter optimization problem of K-nearest neighbors classifier 2 against very common Breast Cancer Wisconsin (Diagnostic) Data Set 3.
Grega Vrbančič
Last updated on Oct 2, 2019 10 min read Guides
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