One of the most common kinds of big data in large-scale data analysis are multi-dimensional point sets. Fundamental operations on point sets include: nearest neighbor search, searching uncertain data, dimension reduction, and clustering. We aim to design, analyze, implement, and evaluate approaches to these point-set problems through a collaborative research in computer science, mathematics, and statistics and other scientific disciplines.