时间：2019年10月31（星期四）14：00-15：00

地点：学院南路校区，学院南路图配楼514会议室

报告人：何煦,、中国科学院数学与系统科学研究院

报告摘要：In this talk, I will present several recent works of mine on constructing experimental design for computer experiments. Computer experiments are computer programs that simulate real systems using mathematical models. Some such simulations are extremely slow in computation, calling for experimental designs that are efficient in building surrogate models. Some recent work suggests that space-filling designs with low fill distance, high separation distance, and certain projective properties are appealing for computer experiments. Usually, such designs are generated using global optimization techniques. However, because the optimization problem is fundamentally difficult, near optimal designs are rarely obtained. My approach is to use lattices that have distance properties in Euclidean space to construct space-filling designs. Such designs include rotated sphere packing designs and interleaved lattice-based designs.

报告人简介：马何煦, 中国科学院数学与系统科学研究院副研究员，中国工业与应用数学学会不确定性量化专委会常务理事，中国现场统计研究会试验设计分会理事。研究方向为计算机实验的设计与分析。本科毕业于北京大学数学科学学院（2007年），博士毕业于威斯康星大学麦迪逊分校（2012年）。以第一作者身份在Annals of Statistics, Journal of the American Statistical Association, Biometrika等统计学顶级期刊发表论文多篇。获得关肇直青年研究奖, 入选陈景润未来之星计划。主持国家自然科学基金面上项目和青年项目。

本次活动受中央财经大学2019专题学术讲座项目资助。