The winners are chosen by these jury members who will keep in mind a number of arguments like the model accuracy, performance, data exploration phase, visuals, relevance etc.

Gert De Geyter

Gert De Geyter is a Senior Consultant Data Analytics at Deloitte, co-organiser of Data Science Ghent and an invited lecturer “Python and Data Analytics” at Toulouse School of Economics and IAE school of management. Gert holds a PhD in Astronomy where he focused on applying machine learning to automatically constructive 3D models of galaxies including radiative transfer based on multi-wavelength observations.

https://www.linkedin.com/in/gertwldegeyter/

Maarten Baes 

Maarten Baes is professor of astronomy at Ghent University since 2005. His research interests include interstellar dust, radiative transfer, infrared astronomy, and galaxy evolution. He is pursuing both theoretical and observational astronomical research, and is involved in several instrumentation projects, both for ground-based telescopes and space missions. He has authored more than 250 publications, and successfully supervised more than 10 PhD and about 40 master theses.

http://users.ugent.be/~mbaes/Home.html

Matthias Feys

Matthias Feys is head of data science at Datatonic, a Specialized Machine Learning Partner of Google. With his team Matthias helps corporations unleashing the power of data using Tensorflow and other Google technologies. Prior to joining datatonic, he did research on Deep Learning for Natural Language Processing.

Geert-Jan Bex

Geert Jan Bex is working for the VSC (Vlaams Supercomputer Centum) speding most of his time on supporting researcher, and providing training. In a previous life, he did research into the statistical physics of neural networks, and worked as knowledge engineer for an IP company. Although currently no longer active in the domain, he still has a keen interest in machine learning.