Dr George Azzopardi

Dr George Azzopardi

Dr George Azzopardi

As of March 2015 I am an Academic Resident (Lecturer) at the Intelligent Computer Systems department of the ICT Faculty in the University of Malta. I am involved in lecturing courses about intelligent interfaces, pattern recognition and computer vision. I am also affiliated with the University of Groningen in the Netherlands where I co-supervise PhD and Masters students.

Together with my collaborators from the Universities of Groningen and Wageningen (the Netherlands), I am the recipient of a ~EUR500k research grant, which we received from the Breed4Food program of STW in the Netherlands. The project is called SMARTBREED - Smart animal breeding using advanced machine learning. More details can be found in here.

Before my current position I was a research innovator at TNO (4 days per week) and a post-doc researcher/lecturer at University of Groningen (one day per week), in the Netherlands. At TNO I was involved in optimization, signal processing, predictive modeling and computer vision projects.

I received a PhD cum laude in Computer Science from University of Groningen (Netherlands) in April 2013. During my studies I developed novel trainable pattern recognition algorithms and published my work on high ranking peer-reviewed journals including IEEE Transactions on Pattern Analysis and Machine Intelligence and Medical Image Analysis. The thesis can be downloaded from http://www.cs.rug.nl/~george/#Downloads.

In 2006 I received a BSc degree (first class honours) in Computer Science and in 2008 I received an MSc degree with distinction in Computer Vision, both from University of London. For the BSc degree I received an academic award for my outstanding achievement and for the MSc degree I ranked first.

Between the year 2000 and 2007, I was a full-time software developer at Bank of Valletta (Malta) and for more than three years I was a scientific developer (part-time) at Iteanova Ltd.

I am open for collaborations with academic and industrial organisations. Feel free to send me an email.
  • Pattern Recognition
  • Computer Vision
  • Brain-inspired algorithms
  • Machine Learning
  • Data Analytics
  • Medical Image Analysis
  • Audio Analysis

Azzopardi, G., Strisciuglio, N., Vento, M. & Petkov, N. 2015, "Trainable COSFIRE filters for vessel delineation with application to retinal images", Medical image analysis, vol. 19, no. 1, pp. 46-57.

Azzopardi, G. & Petkov, N. 2014, "Ventral-stream-like shape representation: from pixel intensity values to trainable object-selective COSFIRE models.", Front Comput Neurosci, vol. 8, pp. 80.

Azzopardi, G., Rodríguez-Sánchez, A., Piater, J. & Petkov, N. 2014, "A Push-Pull CORF Model of a Simple Cell with Antiphase Inhibition Improves SNR and Contour Detection", PLoS ONE, vol. 9, no. 7, pp. e98424.

Azzopardi, G. & Petkov, N. 2014, "COSFIRE: A Brain-Inspired Approach to Visual Pattern Recognition", Lecture Notes in Computer Science, Brain-Inspired Computing
, eds. Gr, L. inetti, T. Lippert & N. Petkov, Springer, , pp. 76-87.

de Vries, H., Azzopardi, G., Koelewijn, A. & Knobbe, A. 2014, "Parametric Nonlinear Regression Models for Dike Monitoring Systems", Lecture Notes in Computer Science, Advances in Intelligent Data Analysis XIII, eds. H. Blockeel, M. van Leeuwen & V. Vinciotti, Springer International Publishing, , pp. 345-355.

Azzopardi, G. & Petkov, N. 2013, "Automatic detection of vascular bifurcations in segmented retinal images using trainable COSFIRE filters", Pattern Recognition Letters, vol. 34, no. 8, pp. 922-933.

Azzopardi, G. & Petkov, N. 2013, "A shape descriptor based on trainable COSFIRE filters for the recognition of handwritten digits", Computer Analysis of Images and Patterns (CAIP 2013) Lecture Notes in Computer Science, pp. 9.

Azzopardi, G. & Petkov, N. 2013, "Trainable COSFIRE filters for keypoint detection and pattern recognition", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 2, pp. 490-503.

Azzopardi, G. & Petkov, N. 2012, "A CORF computational model of a simple cell that relies on LGN input outperforms the Gabor function model", Biological cybernetics, vol. 106, no. 3, pp. 177-189.

Azzopardi, G. & Smeraldi, F. 2009, "Variance Ranklets: orientation-selective rank features for contrast modulations", British Machine Vision Conference (BMVC).



  • University of Groningen

Ongoing collaborations

  • University of Innsbruck

  • University of Leon

  • University of Salerno

  • University of Cyprus

  • University of Wageningen

Erasmus Agreements

  • I have established Erasmus Agreements with the Universities of Groningen, Salerno, Cordoba, Leon,
    and Warsaw University of Life Sciences. Feel free to contact me if you are interested to apply for Erasmus to go to any one of these

Start PhD Studies?

  • If you have pre-secured a fellowship/scholarship/studentship paying your own salary or intend to
    apply for one, and your research interests match any of the below topics, then please feel free to send me an email.

  • We may also apply together for a PhD scholarship from the University of Groningen, where I am
    also affiliated. In that case, the PhD student will have funds for two years on full-time basis.

Topics of interest

  1. Brain inspired computer vision

  • contour detection, segmentation, object recognition, image classification, tracking, …

  • Medical Image Analysis

    • retinal images, mammography, x-rays, ...

  • Pattern recognition

    • Audio and/or video analysis

  • Big data analytics

    • data fusion, data mining, …