dr. Christina Papagiannopoulou

Christina PapagiannopoulouResearch team: Hydrology and Climate

I graduated from the University of Ioannina, Greece, with a bachelor degree in Computer science. Afterwards, I obtained my Master of Science in Computer Science at Aristotle University of Thessaloniki, Greece. During my master studies, I focused on studying the mathematical background of machine learning, while my master thesis topic was about multi-label classification problems. Then, I worked as a research assistant at Information Technologies Institute (ITI), Center of research and Technology – Hellas. At ITI I worked on various projects related to image processing. In 2014, I joined the Research Unit Knowledge-Based Systems, Department of Data Analysis and Mathematical Modelling, Faculty of Bioscience Engineering, as a PhD student. Funded by the Belgian Federal Science Policy Office (Belspo), my research was conducted within the framework of the SAT-EX project, in a close collaboration with the Laboratory of Hydrology  and Water Management, Department of Environment, Faculty of Bioscience Engineering. My work focused on the study of machine learning methods on climate data. Specifically, during my PhD, I investigated the relationship between climate and vegetation by using a causality analysis for each location of the Earth separately. To this end, I developed a novel framework which combines several components, such as data collection from various databases and predictive modelling approaches. Moreover, I modeled the dynamic interplay between vegetation and local climate in order to delineate ecoregions that share a coherent response to hydro-climate variability. My current interests include the study of extreme events and their causal relationships with climate or other factors.


Research topics: machine learning, biosphere–climate interactions.




  • 2018 – Present: Postdoctoral Researcher, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
  • 2014 – 2018: PhD, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
  • 2013 – 2014: Research Associate, Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI), Thessaloniki, Greece
  • 2011 – 2013: Master in Computer Science, Aristotle University of Thessaloniki, Thessaloniki, Greece
  • 2007 – 2011: Bachelor in Computer Science, University of Ioannina, Ioannina, Greece
  • 2010 – 2011: Programmer, Department of Informatics of the Prefecture of Ioannina, Ioannina, Greece


  • SAT-EX


  1. Papagiannopoulou, C., Miralles, D. G., Demuzere, M., Verhoest, N. E. C., Waegeman, W. Global hydro-climatic biomes identified via multi-task learning, Geoscientific Model Development, 11, 4139–4153, 2018..
  2. Papagiannopoulou, C., Miralles, D. G., Decubber, S., Demuzere, M., Verhoest, N. E. C., Dorigo, W. A., Waegeman, W. A non-linear Granger-causality framework to investigate climate-vegetation dynamics, Geoscientific Model Development, 10, 1945-1960, 2017.
  3. Papagiannopoulou, C., Miralles, D. G., Dorigo, W. A., Verhoest, N. E. C., Depoorter, M., Waegeman, W. Vegetation anomalies caused by antecedent precipitation in most of the world, Environmental Research Letters, 12, 7, 2017.
  4. Papagiannopoulou, C., Decubber, S., Miralles, D. G., Verhoest, N., Dorigo, W., Waegeman, W. Analyzing Granger Causality in Climate Data with Time Series Classification Methods. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Springer, 15-26, 2017.
  5. Papagiannopoulou, C., Tsoumakas, G., Tsamardinos, I. Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning. Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 915-924, 2015.