Dr. Xanthoula Eirini Pantazi an Associate Professor in Laboratory of Agricultural Engineering, Aristotle University, School of Agriculture, Greece. She holds a PhD in Biosystems Engineering and is an expert in bio-inspired computational systems and data mining. Her research interests include sensor & data fusion, IoT data handling & management, Machine Learning and Artificial Intelligence models, for precision farming applications including yield prediction, postharvest quality assessment, plant stress detection and non-destructive sensing of bio-material and crop protection. She has been involved in several EU projects and ERANET and has developed apps for FIWARE future Internet applications based on Neural Network applications. Her recent research interests consider bioinformatic applications in field phenotyping with autonomous platforms (e.g. UAV, robots) and application of active learning in a number of sectors
from condition monitoring, crop status determination, weed species recognition as well as post-harvest quality determination. She has been involved to the formation of DSS prototype systems for the application of hydro-fertilization and crop protection application in variable rates. Her publications in peer-reviewed international journals, collective volumes and conference proceedings exceed 50 (>3000 citations, h-index 21). She has participated in >18 research projects funded by national funding bodies and she has served as coordinator of the HORIZON 2020 project SiEUSOIL (Sino- EU Soil Observatory for intelligent Land Use Management, Grant agreement no: 818346). She is the main author of the monograph “Intelligent Data Mining and Fusion Systems in Agriculture” (ISBN: 9780128143919).
Dr. Xanthoula Eirini Pantazi an Associate Professor in Laboratory of Agricultural Engineering, Aristotle University, School of Agriculture, Greece. She holds a PhD in Biosystems Engineering and is an expert in bio-inspired computational systems and data mining. Her research interests include sensor & data fusion, IoT data handling & management, Machine Learning and Artificial Intelligence models, for precision farming applications including yield prediction, postharvest quality assessment, plant stress detection and non-destructive sensing of bio-material and crop protection. She has been involved in several EU projects and ERANET and has developed apps for FIWARE future Internet applications based on Neural Network applications. Her recent research interests consider bioinformatic applications in field phenotyping with autonomous platforms (e.g. UAV, robots) and application of active learning in a number of sectors
from condition monitoring, crop status determination, weed species recognition as well as post-harvest quality determination. She has been involved to the formation of DSS prototype systems for the application of hydro-fertilization and crop protection application in variable rates. Her publications in peer-reviewed international journals, collective volumes and conference proceedings exceed 50 (>3000 citations, h-index 21). She has participated in >18 research projects funded by national funding bodies and she has served as coordinator of the HORIZON 2020 project SiEUSOIL (Sino- EU Soil Observatory for intelligent Land Use Management, Grant agreement no: 818346). She is the main author of the monograph “Intelligent Data Mining and Fusion Systems in Agriculture” (ISBN: 9780128143919).
Ν005Υ-Mathematics (Undergraduate)
Ν225Ε,447Ε Automation Priciples-New Technologies (Undergraduate)
N221E- Drying and Storage of Agricultural Products (Undergraduate)
N075E-Precision Agriculture-Saving Resources (Undergraduate)
Ν209Υ, Ν250Υ - Farm Machinery Management
N236E-Electric Motors and Pumps (Undergraduate)
Ν238Ε-Mechanic Harvesting of Farm Crops (Undergraduate)
Forecasting of Fusarium Head Blight spatial distribution in winter wheat using machine learning
A., Morellos, X.E., Pantazi, M.B., Almoujahed, Z., Kriauciuniene, M., Kazlauskas, E., Šarauskis, A.M. Mouazen
Journal Papers
Early detection of bacterial canker in tomato plants using spectroscopy for smart agriculture applications
P., Papazoglou, I., Navrozidis, S., Testempasis, X.E., Pantazi, A., Lagopodi and T. Alexandridis
Journal Papers
A hybrid LSTM approach for irrigation scheduling in maize crop
K., Dolaptsis, X.E., Pantazi, C., Paraskevas, S., Arslan, Y., Tekin, B.B., Bantchina, Y., Ulusoy, K.S., Gündoğdu, M., Qaswar, D., Bustan and A.M. Mouazen A.M
Journal Papers
Non-Destructive Quality Estimation Using a Machine Learning-Based Spectroscopic Approach in Kiwifruits
G., Tziotzios, X.E., Pantazi, C.Paraskevas, C., Tsitsopoulos, D.,Valasiadis, E., Nasiopoulou, M., Michailidis, A., Molassiotis
Journal Papers
An IoT Transfer Learning-Based Service for the Health Status Monitoring of Grapevines. Applied Sciences
A., Morellos; K., Dolaptsis; G., Tziotzios; X.E., Pantazi; D., Kateris; R., Berruto; & D., Bochtis
Journal Papers
Technological development and commercial implementation of a quality protocol for the export of Greek kiwifruit to important market-Premium Kiwi
Potential of selective harvest based on mycotoxins content assessment in cereal crops -POSHMyCo
An interlinked digital platform for Food Integrity and Traceability of relevant MEDIterranean supply chains -MEDIFIT
High performance computing services for prevention and control of pests in fruit crops- GRAPEVINE
INEA
European e-Infrastructure for Extreme Data Analytics in Sustainable Development -EUXDAT
Horizon 2020
Screening defense responses in tomato, triggered by encapsulated biological control agents and organic defense inducers, with the use of Artificial Neural Networks
Monitoring of surface-waters with remote sensing for the rational use of insecticides in wide area mosquito control-WAMOS