Professor, Mathematics, Psychology
Prof. Zhang develops algebraic and geometric methods for data analysis. Algebraic methods are based on theories of topology and partially ordered sets (in particular lattice theory); an example being formal concept analysis (FCA). Geometric methods include Information Geometry, which studies the manifold of probability density functions. Zhang also has interests in machine learning, including reproducing kernel Banach space (RKBS) and reinforcement learning (RL).