讲座人简介：张日权，华东师范大学统计学院院长，教授，博士生导师。担任教育部统计与数据科学前沿理论及应用重点实验室主任，中国现场统计研究会大数据统计分会理事长，中国商业统计学会数据科学与商业智能分会副理事长，上海统计学会副会长，《应用概率统计》期刊常务副主编。主持多项国家自然科学基金、教育部博士点基金、国家统计局重点项目等研究项目20多项；发表论文170余篇，SCI收录论文130余篇，出版专著2部，教材2部。先后获得上海市育才奖，上海市自然科学奖三等奖，上海市教学成果一等奖。主要研究方向：大数据统计，金融统计，非/半参数统计，超/高维数据分析，函数型数据分析、统计机器学习。

讲座简介：The rapid emergence of massive datasets in various fields poses a serious challenge to traditional statistical methods. Meanwhile, it provides opportunities for researchers to develop novel algorithms. Inspired by the idea of divide-and-conquer, various distributed frameworks for statistical estimation and inference have been proposed. They were developed to deal with large-scale statistical optimization problems. This report aims to provide a comprehensive review for related literature. It includes parametric models, nonparametric models, and other frequently used models. Their key ideas and theoretical properties are summarized. The trade-off between communication cost and estimate precision together with other concerns are discussed.