Jiann-Ming Wu is a mathematics educator in Taiwan. He currently serves National Dong Hwa University as a professor and head in the department of Applied Mathematics. In addition to holding a career in education, Dr. Jiann-Ming is known for the design of multilayer Potts perceptrons, generalized adalines, natural elastic nets, Mahalanobis-NRBF neural networks, state-regulated inverse neural networks, Potts ICA neural networks, Sudoku associative memory, and deep learning, inluding annealed Kullback-Leibler divergence minimization learning, annealed cooperative-competitive learning, hybrid mean-field-annealing and gradient descent deep learning, among others. Prior to entering a career in mathematics education, Dr. Jiann-Ming received a Bachelor of Science in Engineering and Computer Science from National Chiao Tung University in 1988. He went on to attend National Taiwan University, where he completed a Master of Science in Computer Science and Information Engineering in 1990 and a PhD in 1994. Dr. Jiann-Ming is certified in engineering through the International Neural Network Society.