Mehdi Gholamnia is a postdoctoral fellow at University College of Dublin working under the guidance of Professor Francesco Pilla. His research focuses on CAMEO (create an architecture for manipulating Earth observation data).His research interests are broad and include remote sensing data analysis, pattern recognition and machine learning, Geospatial processing, statistical and mathematical modeling, and time series and signal processing techniques.He completed his PhD in Remote Sensing and GIS from the University of Tehran. Over the past 10 years, he has also taught surveying engineering modules for the BSc degree in Azad University of Kurdistan, and for the last four years, he has been teaching Pattern Recognition and Machine Learning” and “Spectroscopy and Hyperspectral Image Processing” to master’s students at Kurdistan University.He is proficient in programming languages such as MATLAB, Python, and R, and he programs with Google Earth Engine (in both Python and JavaScript platform). His strongest area is time series analysis and geospatial processing, especially in ecological applications and environmental modeling. In one of his research projects, he extracted vegetation phenological parameters and their interactions with climate effects using the TIMESAT and Breakfast algorithms.In addition to teaching and research, he has worked on a range of spatial analysis projects. For example, he has implemented spatial analysis using PostGIS in PostgreSQL on a Python-based platform, and to manage and visualize the results of remote sensing analyses, he has connected Django, Geoserver, and PostgreSQL.In terms of his programming expertise, he uses Python programming packages such as Geemap, geopandas, Keras, and scikit-learn, as well as Django as a backend and HTML, CSS, and JavaScript for frontend development. He also uses Geoserver to publish maps in WFS and WMS formats.As a researcher, he is passionate about exploring new frontiers in remote sensing and GIS and finding innovative solutions to real-world problems.
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