Assist. Prof. Dr Xanthoula Eirini Pantazi | Materials Science | Best Researcher Award
๐พ Dr. Xanthoula Eirini Pantazi is an Assistant Professor at Aristotle University of Thessaloniki, specializing in precision agriculture, artificial intelligence, and biosystems engineering. ๐ She holds a Ph.D. in Biosystems Engineering and has contributed extensively to AI-driven agricultural solutions, machine learning, and sensor fusion. ๐ 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. ๐ฑ She has received prestigious scholarships and keynote speaker invitations at international conferences. ๐ Her research continues to advance smart farming and sustainable agriculture. ๐๐ก
Assist. Prof. Dr Xanthoula Eirini Pantazi Aristotle University of Thessaloniki, School of Agriculture Greece
Profile
Experienceย ๐
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. ๐๏ธ From 2016 to 2019, she worked as an Adjunct Lecturer, teaching undergraduate courses in agricultural engineering. ๐ 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). ๐ฌ๐พ
Scholarly Contributions โ๏ธ๐ฌ
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. ๐พ๐ก 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. ๐๐ค
๐ก Scientific Research ๐ฌ๐พ
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. ๐๐ 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. ๐๐ค
Research Focus ๐โจ
Assist. Prof. Dr. Xanthoula Eirini Pantazi’s research focuses on applying machine learning, advanced sensing, and data fusion in agriculture ๐พ๐ป. Key areas include crop yield prediction using machine learning and sensing techniques ๐๐ฑ, disease detection in plants through image analysis and spectroscopy ๐ฆ ๐ฌ, and weed recognition using hyperspectral sensing and UAV imagery ๐๐พ. She also works on soil health monitoring and water stress detection using multisensor fusion ๐ง๐. Dr. Pantazi’s contributions aim to optimize agricultural practices through innovative technologies, improving sustainability and precision in farming ๐ฟ๐.
Publications ๐
Forecasting of Fusarium head blight spatial distribution in winter wheat using machine learning
Authors: Morellos, A., Pantazi, X.E., Almoujahed, M.B., ล arauskis, E., Mouazen, A.M.
Journal: Computers and Electronics in Agriculture (2025)
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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)
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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)
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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)
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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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