Marko Mihajlovic received his M.Sc. in Computer Science and Information Technology from the School of Electrical Engineering, University of Belgrade, and has been pursuing his Ph.D. in Intelligent Software Engineering at Singidunum University since 2023. Throughout his academic work, he has published multiple peer-reviewed papers and presented at scientific conferences, contributing to research areas such as photovoltaic power forecasting, phishing detection using XGBoost, sentiment analysis in natural language processing, and optimization methods in computer vision. His research primarily focuses on machine learning, neural networks, computer vision, natural language processing, and metaheuristic optimization. A highlighted contribution is his flagship work on Spatial Mask Merging (SMM), a graph-based algorithm optimized with R-tree spatial indexing that addresses fragmentation and duplication in high-resolution instance segmentation. This method significantly improves mask consistency in tiled inference pipelines and stands as one of his key doctoral research achievements. The full paper, “Enhancing Instance Segmentation in High-Resolution Images Using Slicing-Aided Hyper Inference and Spatial Mask Merging Optimized via R-Tree Indexing,” is available at: https://www.mdpi.com/2227-7390/13/19/3079