Research Assistant

Eftichia Badeka received her diploma in Computer Engineering, specializing in Industrial Informatics, from the Technological Educational Institute of Serres in 2015. During her studies, she undertook her thesis supervised by Dr. Ioannis Kalomoiros on the topic of “Study and Implementation of Software for Point Feature Detectors from Images for Object Recognition in Computer Vision Applications,” where she conducted research on the SIFT algorithm by David Lowe and implemented it in Matlab.
Professionally, E. Badeka worked in computer and network services from 2012-2013 at Computer Lab – CHRISTOFORIDIS A. AND CO OE, and until 2015, she worked as a freelance professional focusing on computer repairs (both hardware and software).
In 2017, she completed a postgraduate program in “Advanced Computer and Information Technologies” at the International University of Kavala (formerly the Technological Educational Institute of Eastern Macedonia and Thrace). Her thesis focused on machine learning on medical retinal images, specializing in pattern recognition methodologies under the supervision of Dr. Georgios Papakostas.
Since 2018, she has been a member of the Human-Machine Interaction Laboratory  at the Department of Informatics and Computer Engineering, International University of Kavala. From 2018 to 2020, she worked on the research project “Personalized Optimal Vineyard Harvest with Autonomous Robot” (T1EDK-00030) under the “RESEARCH-CREATE-INNOVATE” where she implemented computer vision algorithms for the visual recognition needs of the autonomous robot, using Python programming environment.
Additionally, from 2020 to 2023, she has been involved in the research project “Technology for Precision Viticulture” (TEGEA) under the “Strengthening Research and Innovation Infrastructures” Action in the Operational Program “Competitiveness, Entrepreneurship and Innovation ” with project code MIS 5046047. She worked as a programmer in computer vision, focusing on species recognition in precision viticulture. Within this project, she studied  neural networks for estimating grape maturity, resulting in the publication of an article titled “A Deep Learning Approach for Precision Viticulture, Assessing Grape Maturity via YOLOv7.” Moreover, her project has passed as a business idea within the framework of the THEKLA incubator. From February 2024 she is working as a research assistant at the Institute of Information and Communication Technologies of the National Centre for Research and Technological Development.
Eftichia Badeka’s interests are photography while she has attended photography courses (2010-2015) at the Former Photographic Laboratory of Serres. She holds a Proficiency certificate in English and has knowledge of German. She has also dabbled in video shooting and editing. Her research interests include computer vision, artificial intelligence, robotics, digital signal/image processing, and pattern recognition.