【摘要】Motivated by a problem in the synthesis of nanowires, a sequential space filling design, called Sequential Minimum Energy Design (SMED), is proposed for exploring and searching for the optimal conditions in complex black-box functions. The SMED is a novel approach to generate designs that are model independent, can quickly carve out regions with no observable nanostructure morphology, allow for the exploration of complex response surfaces, and can be used for sequential experimentation. It can be viewed as a sequential design procedure for stochastic functions and a global optimization procedure for deterministic functions. The basic idea has been developed into an implementable algorithm, and guidelines for choosing the parameters of SMED have been proposed. Convergence of the algorithm has been established under certain regularity conditions. Performance of the algorithm has been studied using experimental data on nanowire synthesis as well as standard test functions.

(Joint work with V. R. Joseph, Georgia Tech and T. Dasgupta, Harvard U.)

【报告人简介】吴建福现任美国佐治亚理工学院工业与系统工程学院Coca Cola 讲座教授，兼任美国统计界最高奖COPSS奖委员会主席、美国COPSS Fisher讲座委员会委员、统计学会Deming讲座委员会委员；1987年获得COPSS奖（国际统计学四十岁以下学者的最高成就奖），2000年被选为中国台湾“中研院”院士，2004年作为第一位统计学者当选美国国家工程院院士，也是第一位华人统计学者获此殊荣。此外，他还获得过多项国际顶级奖励。学术界对他的评价是：“他的贡献始终是专业严格性与实际重要性的理想结合”；吴建福“创建了一套现代实验设计体系，培养了一代质量科学专业工作者和教授”。