Workshop on Applications-Driven Geometric Functional Data Analysis

该奖项支持参加2017年10月8日至10日在佛罗里达塔拉哈西的佛罗里达州立大学校园举行的为期三天的应用驱动几何功能数据分析（FDA）研讨会。该研讨会的重点是FDA，无限维微分几何和数据驱动应用的交叉点的主题，并将具有来自这些领域的高级专家和初级研究人员。 讲习班包括半天的辅导，介绍讲习班的主题，特别是针对初级研究人员。 其余时间将分配给特邀演讲，海报会议和讨论会。本次研讨会的主要动机是发起和促进具有不同背景和专业知识的美国科学家和数学家之间的讨论和未来合作。组织者将通过瞄准研讨会三个组成领域的领先专家-几何学，FDA和大数据分析，努力实现广度和多样性。海报会议将用于鼓励所有参与者，特别是初级研究人员，介绍他们的研究和与他人互动。 从自然科学和社会科学到工程和技术，所有学科中功能数据的快速增长使FDA成为一个重要的研究课题。为了应对FDA面临的各种挑战，需要利用功能数据中存在的低维模式和结构。几何图形提供的工具可用于：（1）提取和分析函数数据中的结构，（2）处理函数空间的无限维，（3）获得可行的统计模型并进行有效的推断;以及（4）处理与许多当前和未来以数据为中心的应用程序相关的大型数据集。 研讨会将包括：（1）理论主题，如无限维空间的几何形状，不变度量下的分析，以及涉及功能数据的统计模型;（2）应用，如计算解剖学，生物信息学，生物识别学和神经科学。这种重要和互补的主题的融合使研讨会成为一个独特和有价值的活动。 有关研讨会的更多信息，请访问https://ani.stat.fsu.edu/GFDW/

This award supports participation in a three-day workshop on applications-driven geometric functional data analysis (FDA) held October 8-10, 2017 on the campus of Florida State University in Tallahassee, Florida. The workshop focuses on topics in the intersections of FDA, infinite-dimensional differential geometry, and data-driven applications, and will feature both senior experts and junior researchers from these areas. The workshop includes a half-day of tutorials providing an introduction to the workshop topics, especially aimed at junior researchers. The remaining time will be allocated to invited talks, a poster session, and discussion sessions. The main motivation for this workshop is to initiate and facilitate discussions and future collaborations between US scientists and mathematicians with different backgrounds and expertise. The organizers will strive for breadth and diversity by targeting leading experts in the three components areas of the workshop -- geometry, FDA, and big data analysis. The poster session will be used to encourage all participants, especially the junior researchers, to present their research and interact with others. A rapid growth of functional data in all disciplines, ranging from natural and social sciences to engineering and technology, has made FDA an important topic of research. To handle the diverse challenges facing FDA, there is a need to exploit low-dimensional patterns and structures present in functional data. Geometry provides tools to: (1) extract and analyze structures in functional data, (2) handle the infinite-dimensionality of function spaces, (3) arrive at viable statistical models and make efficient inferences; and (4) process large datasets associated with many current and future data-centric applications. The workshop will include both: (1) theoretical topics, such as geometries of infinite-dimensional spaces, analysis under invariant metrics, and statistical models involving functional data; and (2) applications, such as computational anatomy, bioinformatics, biometrics, and neuroscience. This blend of important and complementary topics makes the workshop a unique and worthwhile event. For more information about the workshop, please refer to https://ani.stat.fsu.edu/GFDW/