Ioannis Moutsinas is an Agricultural Engineer and Ph.D. candidate at the Department of Agriculture, Crop Production and Rural Environment, at the University of Thessaly. He graduated from the School of Agricultural Sciences of the University of Thessaly in 2013 and received his M.Sc. in Biosystems Engineering from the Farm Technology Group at Wageningen University & Research in 2015. Since 2016, he has been working at the Networks & Telecommunications Laboratory (NITLab) at the University of Thessaly as an Agricultural Engineer - Researcher, and Project Manager. Prior to joining NITLab, he worked both in a floriculture greenhouse and in an agricultural consultancy office for livestock farms in Greece and the Netherlands. Since 2020, Ioannis has also been a certified Agricultural Advisor. His research interests focus on the design, integration, and application of Internet of Things (IoT) and Remote Sensing technologies in agriculture, aiming to enhance sustainability, environmental management, and productivity in the primary sector. Throughout his research career, he has actively contributed to interdisciplinary research and innovation activities, including consortium development, stakeholder engagement, project management, resource coordination, data analysis, and impact assessment. To date, he has participated in more than 20 funded Research & Development projects related to Precision Agriculture, Climate-Smart Agriculture, and environmental sustainability. His doctoral research focuses on the assessment of the phenological responses of major fruit crops to climate variability and climate change by employing advanced IoT and Remote Sensing technologies. Through his research, Ioannis aims to contribute to the development of data-driven and climate-resilient agricultural systems that support sustainable food production and informed decision-making in modern agriculture.

As a Fulbright Visiting Research Student he will be engaged in a 6-month research project aimed at developing and validating real-time edge AI models for nutrient estimation in citrus orchards using UAV-based hyperspectral imaging, integrating advanced AI techniques for canopy segmentation, nutrient prediction, edge device deployment, and prescription map generation to enhance precision agriculture.