Assist. Prof. Dr Xanthoula Eirini Pantazi | Materials Science | Best Researcher Award
πΎ Dr. Xanthoula Eirini Pantazi is an Assistant Professor at Aristotle University of Thessaloniki, specializing in precision agriculture, artificial intelligence, and biosystems engineering. π She holds a Ph.D. in Biosystems Engineering and has contributed extensively to AI-driven agricultural solutions, machine learning, and sensor fusion. π Dr. Pantazi has been involved in 20+ EU-funded projects, including Horizon 2020 initiatives. Her expertise spans decision support systems, UAV applications, and crop monitoring. π± She has received prestigious scholarships and keynote speaker invitations at international conferences. π Her research continues to advance smart farming and sustainable agriculture. ππ‘
Assist. Prof. Dr Xanthoula Eirini Pantazi Aristotle University of Thessaloniki, School of Agriculture Greece
Profile
ExperienceΒ π
Assist. Prof. Dr. Xanthoula Eirini Pantazi has an extensive academic and research background in precision agriculture and bio-systems engineering. Since 2020, she has been an Assistant Professor at the Faculty of Agriculture, Forestry, and Natural Environment at Aristotle University of Thessaloniki, Greece. ποΈ From 2016 to 2019, she worked as an Adjunct Lecturer, teaching undergraduate courses in agricultural engineering. π Additionally, she served as a Research Engineer and Technical Manager at CERTH (2016-2020) and contributed to major EU-funded research projects as a Research Engineer at Aristotle University (2013-2020). π¬πΎ
Scholarly Contributions βοΈπ¬
Assist. Prof. Dr. Xanthoula Eirini Pantazi has significantly contributed to the field of precision agriculture and artificial intelligence through her numerous book chapters. Her work includes data fusion for soil and crop sensing, leaf disease recognition using machine learning, and hyperspectral sensing for weed and crop differentiation. πΎπ‘ She has co-authored chapters in Springer and Wageningen Academic Publishers, focusing on AI applications in farming, sustainable agriculture, and bioinformatics. Her expertise in remote sensing, spectral data analysis, and machine learning models has helped develop innovative solutions for smart farming and soil health monitoring. ππ€
π‘ Scientific Research π¬πΎ
Assist. Prof. Dr. Xanthoula Eirini Pantazi has led and contributed to numerous EU-funded and international research projects in precision agriculture, AI-driven crop monitoring, and smart farming solutions. As a principal investigator and work package leader, she has developed machine learning models for disease detection, decision support systems (DSS) for sustainable farming, and sensor fusion techniques for soil and crop health assessment. ππ Her projects include Horizon 2020 initiatives (AfriCultuReS, SiEUSOIL, ATLAS, STARGATE), ICT-AGRI ERANET, and PRIMA projects. Her work integrates AI, robotics, and IoT-based solutions, advancing climate-resilient and precision-driven agricultural systems. ππ€
Research Focus πβ¨
Assist. Prof. Dr. Xanthoula Eirini Pantazi’s research focuses on applying machine learning, advanced sensing, and data fusion in agriculture πΎπ». Key areas include crop yield prediction using machine learning and sensing techniques ππ±, disease detection in plants through image analysis and spectroscopy π¦ π¬, and weed recognition using hyperspectral sensing and UAV imagery ππΎ. She also works on soil health monitoring and water stress detection using multisensor fusion π§π. Dr. Pantazi’s contributions aim to optimize agricultural practices through innovative technologies, improving sustainability and precision in farming πΏπ.
Publications π
Forecasting of Fusarium head blight spatial distribution in winter wheat using machine learning
Authors: Morellos, A., Pantazi, X.E., Almoujahed, M.B., Ε arauskis, E., Mouazen, A.M.
Journal: Computers and Electronics in Agriculture (2025)
πΎπ»
Non-Destructive Quality Estimation Using a Machine Learning-Based Spectroscopic Approach in Kiwifruits
Authors: Tziotzios, G., Pantazi, X.E., Paraskevas, C., Michailidis, M., Molassiotis, A.
Journal: Horticulturae (2024)
π₯π
A Hybrid LSTM Approach for Irrigation Scheduling in Maize Crop
Authors: Dolaptsis, K., Pantazi, X.E., Paraskevas, C., Bustan, D., Mouazen, A.M.
Journal: Agriculture (2024)
πΎπ€
Application of Machine Learning for Disease Detection Tasks in Olive Trees Using Hyperspectral Data
Authors: Navrozidis, I., Pantazi, X.E., Lagopodi, A., Bochtis, D., Alexandridis, T.K.
Journal: Remote Sensing (2023)
πΏπ»
Early Detection of Cavitation in Centrifugal Pumps Using Low-Cost Vibration and Sound Sensors
Authors: Karagiovanidis, M., Pantazi, X.E., Papamichail, D., Fragos, V.
Journal: Agriculture (2023)
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