My current research focuses on Geo-spatial Retrieval-Augmented Generation (RAG), where I explore how large language models can be enriched with spatial data and reasoning. Unlike traditional RAG that only leverages textual knowledge, Geo-spatial RAG requires integrating geographic context, spatial databases, and semantic retrieval to answer location-aware and context-rich questions. I am particularly interested in designing frameworks that combine spatial indexing, semantic embeddings, and conversational query reformulation to achieve more accurate, transparent, and interactive responses. This includes addressing challenges such as spatio-temporal constraints, user intent disambiguation, and trustworthy enrichment of queries. More broadly, my research lies at the intersection of data management, geospatial AI, and trustworthy machine learning, with the long-term goal of creating systems that bridge the gap between complex spatial data landscapes and human-centered decision-making. I am always excited to discuss collaborations and new ideas in this space 😃