RTG: Statistics in the 21st Century - Objects, Geometry and Computing

RTG：21世纪的统计学-对象、几何和计算图像、矩阵、函数、轨迹、树或图形是现代数据分析中越来越多遇到的对象的例子。对这些客观数据进行统计分析所需要的技能和知识还不是统计学家标准培训的一部分。这包括现代数据处理技能，如访问网络服务或处理复杂格式的大型数据；在多学科科学环境中工作所需的技能；以及数学技能，特别是涉及几何、形状或拓扑的概念。该项目为本科生和研究生提供培训，通过应用于重要科学问题的数据分析、接触先进方法的研究、相应的相关数学理论和计算来解决这些问题。研究生和博士后研究员还接受教学、指导、科学写作和沟通技能方面的培训，以及其他对成功的学术生涯至关重要的方面的培训，如拨款撰写和工作申请。持续的技术进步伴随着新的、复杂的数据类型的迅速增加，发展分析所需技能的重要性怎么强调都不为过。几何和计算的各个方面往往是这种分析的中心。因此，该项目正在大力推进与分析这类现代数据类型有关的培训，从而努力为广泛的现代统计培训提供一个范本。该项目建立在高级人员、附属成员和来自应用数学、天文学、生物人口学、计算机科学和神经科学等科学领域的合作者的经验和优势的基础上。培训活动不仅将进一步加强加州大学戴维斯分校的统计课程，还将为加强STEM学科的劳动力做出重要贡献。

RTG: Statistics in the 21st Century - Objects, Geometry and ComputingImages, matrices, functions, trajectories, trees, or graphs are examples of objects increasingly encountered in modern data analysis. Statistical analysis of such object data requires skills and knowledge that are not (yet) part of a standard training of a statistician. This includes modern data handling skills, such as accessing web services, or manipulating large data in complex formats; skills needed for working in a multi-disciplinary scientific environment; and also mathematical skills, in particular involving notions of geometry, shape or topology. The project provides training to undergraduate and graduate students, addressing these issues through data analysis applied to important scientific questions, exposure to research in advanced methodologies, corresponding relevant mathematical theories, and computing. Graduate students and postdoctoral fellows also receive training in teaching, mentoring, scientific writing and communication skills, and also in other aspects that are essential for a successful academic career, such as grant writing and job application.Continuous technological advances go hand in hand with a rapid increase of novel, complex data types, and the importance of developing skills necessary for their analysis cannot be overstated. Aspects of geometry and computing often lie in the center of such an analysis. The project is thus critically advancing training related to the analysis of such modern data types, thereby striving to provide a model for a broad, modern training in statistics. The project builds on the experiences and the strengths of the senior personnel, the affiliated members and collaborators from scientific fields including applied mathematics, astronomy, bio-demography, computer science, and neuroscience. The training activities will not only further strengthen the statistics program at UC Davis, but will also make critical contributions to enhancing the workforce in the STEM disciplines.