Thomas Mortier
After obtaining a master degree in Computer Science and a master degree in Statistical Data Analysis at Ghent University in 2017, Thomas Mortier started as an assistant at the KERMIT research group at the Faculty of Bioengineering Sciences. In addition to obtaining a PhD, he provided support for courses on statistics and machine learning and supervised master and PhD students. He currently works as a researcher, focusing on uncertainty in machine learning with applications in applied biological and climate sciences. He also has experience as a data scientist and is involved in teaching various courses on machine learning at the Ghent University Academy for Engineers (UGain).
Expertise: machine learning, artificial intelligence, data science, statistical data analysis
Field of study/sector
- Computer Science & IT
- Higher Education & Research
- Agriculture, Nature & the Environment
Organisation
Blog posts
Every tree has a fingerprint: combating illegal timber trade
The trade of illegal timber is growing worldwide: timber with unknown origins increasingly finds its way to the market through shady routes. To combat this, Thomas Mortier (UGent) and Victor Deklerck (World Forest ID, Plantentuin Meise) developed an AI model that can trace the origin of timber via a unique ‘chemical fingerprint’. Their research was recently published in the prestigious journal ‘Nature Plants’.