Conference on Topology, Geometry, and Data Analysis at The Ohio State University

摘要奖：DMS 1613094主要研究者：Matthew K. Kahle，Tamal K. Dey，Facundo Memoli，Yusu Wang这个NSF奖项将支持2016年5月在俄亥俄州州立大学举行的“拓扑，几何和数据分析”会议。拓扑学和几何学为理解复杂数据集的形状和结构提供了新颖而强大的方法。本次会议将聚集在代数拓扑，计算几何和相关领域的专家，以及在更多的应用科学领域的研究人员。其主要目的是通过促进合作交流思想和巩固协同活动。组织者将鼓励一些初级参与者的参与，将这一新兴领域介绍给下一代研究人员。大部分资金将用于支付与会者的旅费和当地费用。应用代数拓扑学是一个发展迅速的领域。这次会议将集中讨论几个最有希望的方面。它将汇集计算拓扑学和几何学（网格生成和流形重建，持久同源性和上同调）的专家，理论基础（持久同源性，稳定性和推理的代数和分类观点）的专家，以及在更多应用领域（数学神经科学，分子生物学，材料科学）工作的研究人员。组织者对跨学科的新合作特别感兴趣，例如应用拓扑方法来检测生物数据集中以前未知的结构，因此本次会议的重点是连贯但广泛的。 这次会议的网站可以在这里找到http://www.tgda.osu.edu/tgda-conf-osu.html。

AbstractAward: DMS 1613094Principal Investigators: Matthew K. Kahle, Tamal K. Dey, Facundo Memoli, Yusu WangThis NSF award will support a conference on "Topology, Geometry, and Data Analysis" at Ohio State University in May 2016. Topology and geometry provide novel and robust methods for understanding the shape and structure of complex data sets. This meeting will gather a number of experts in algebraic topology, computational geometry, and related areas, as well as researchers in more applied scientific domains. The main aims are to exchange ideas and to consolidate synergistic activities through fostering collaborations. The organizers will encourage participation by a number of junior participants, introducing this emerging field to the next generation of researchers. Most of the funding will support travel and local expenses of conference participants.Applied algebraic topology is a rapidly developing area. This meeting will focus on a few of the most promising fronts. It will bring together specialists in computational topology and geometry (mesh generation and manifold reconstruction, persistent homology and cohomology), experts in the theoretical underpinnings (algebraic and categorical views of persistent homology, stability and inference), and researchers working in more applied areas (mathematical neuroscience, molecular biology, material science). The organizers are especially interested in new collaborations across disciplines, for example in applying topological methods to detect previously unknown structure in biological datasets, so the focus of this meeting is coherent but broad. The website for this conference can be found here http://www.tgda.osu.edu/tgda-conf-osu.html.