Georgios Dimitrios Gkologkinas

Geospatial Analyst Intern at GEOTOMI, with hands-on experience in geospatial data analysis using machine learning and spatial statistics. Contributed to the integration of cloud-based GIS platforms and supported the development of geospatial visualization workflows. Comfortable working with Python and GIS tools, with a solid analytical mindset and strong interest in real-world geospatial applications. Currently pursuing an MSc in Artificial Intelligence and Data Analytics, with a thesis focused on hyperspectral image classification using deep learning models such as U-Net and its variants. Involved in advanced data analysis using Python and RStudio, and exploring data mining techniques for geospatial intelligence.

Gkologkinas, G.-D., et al. A Python Framework for Crop Yield Estimation Using Sentinel-2 Satellite Data, MDPI AI, Vol. 6, No. 1, 2025. https://www.mdpi.com/2673-4834/6/1/15

Three additional co-authored papers are currently under peer review, expected to be published by the end of summer 2025.

Academic Projects in Machine Learning and Data Analysis
Completed several academic projects as part of the MSc program in Artificial Intelligence and Data Analytics, including:

Supervised and unsupervised learning (e.g. classification, clustering, domain transfer such as zebras-to-horses)

Geospatial data analysis in the Exploratory Data Analysis and Visualization course, involving both tabular and spatial datasets

NoSQL database design and querying, as part of the Network Analysis and Web Data Mining course

📂 Full project documentation and source code are archived and available upon request for further review.