Dr. Gaba is a mathematician and researcher specializing in Applied Algebraic Topology and Geometric Machine Learning. With a strong background in functional analysis, asymmetric topology, and fixed point theory in generalized metric spaces, his research bridges deep mathematical theory with real-world applications. He has published several scientific works exploring topological data analysis (TDA), geometric deep learning (GDL), and stochastic analysis in finance, and is currently advancing geometric and topological methodologies in reinforcement learning, with applications in healthcare and financial systems. His work also includes the study of optimization in geodesic and curved spaces, pushing the boundaries of algorithmic design in complex environments. As both a topologist and applied scientist, Dr. Gaba stands at the intersection of theory and practice, developing rigorous mathematical frameworks while contributing to the advancement of artificial intelligence.