CBMS Regional Research Conference on Topological Data Analysis

“拓扑数据分析：理论与应用”会议将于2017年6月12日至16日在麦卡拉斯特学院（明尼苏达州圣保罗）举行。拓扑数据分析（TDA）是数学、统计学和计算机科学交叉的一个相对较新的快速发展的研究领域。会议的目标是鼓励教师和学生研究TDA，特别是在主要的本科院校，他们可能之前没有TDA的经验。因此，这次会议将吸引来自中西部上游各州的学院和大学的教师、研究生和高级本科生。会议的目的不仅是为与会者提供TDA的理论框架，而且提供实用的计算工具，提供切入点，以便来自不同环境的教师和学生可以开始拓扑数据分析的研究，并将这项工作纳入他们的教学。会议将促进机构之间和跨学科之间的新研究合作。由此产生的专著，由首席讲师，波莫纳学院数学系副教授Vin de Silva博士编写，应该是数学家，科学家和学生感兴趣的。近年来，拓扑数据分析（TDA）引起了数学家和科学家的广泛兴趣，他们正在寻找新的工具来分析来自神经科学、数字成像、遗传学、生物聚集、传感器网络、癌症研究和其他领域日益增长的复杂数据。TDA的智力吸引力来自于它将高等数学、尖端算法和实际应用相结合。然而，尽管它的数学复杂性，TDA方法是令人惊讶的直观，适合与学生一起研究，即使是在本科水平。本次会议的主要讲师将是Vin de Silva博士，他一直是TDA发展的主要贡献者。讲座主题将包括圈数、简单同调和上同调、持续算法、稳定性定理、之字形持续、范畴论和广义持续，以及Reeb协束。除了讲座之外，会议还将举办实验室会议，为与会者提供使用最先进的TDA软件分析真实数据的实践经验，以及展示学生参与的TDA研究的海报会议。这次会议将侧重于数学和计算，而不是统计学，它将强调主要在本科院校进行的研究。有关会议的信息可在http://pages.stolaf.edu/tda-conference/上获得

The conference, "Topological Data Analysis: Theory and Applications," will take place at Macalaster College (St. Paul, MN) from June 12-16, 2017. Topological Data Analysis (TDA) is a relatively recent and quickly-developing area of research at the intersection of mathematics, statistics, and computer science. The goal of the conference is to encourage research in TDA by faculty and students, especially at primarily undergraduate institutions, who might not have prior experience with TDA. As such, this conference will attract faculty, graduate students, and advanced undergraduates from colleges and universities across the upper Midwestern states. The conference is designed to equip attendees with not only the theoretical framework of TDA, but also practical computational tools, providing points of entry so that faculty and students from diverse settings can begin research in topological data analysis and incorporate this work into their teaching. The conference will spur new research collaborations between institutions and across disciplines. The resulting monograph, prepared by principal lecturer Dr. Vin de Silva, Associate Professor of Mathematics at Pomona College, should be of interest to mathematicians, scientists and students. In recent years, Topological Data Analysis (TDA) has attracted widespread interest from mathematicians and scientists looking for new tools to analyze ever increasing amounts of complex data arising from neuroscience, digital imaging, genetics, biological aggregations, sensor networks, cancer research, and other areas. The intellectual appeal of TDA arises from its combination of advanced mathematics, cutting-edge algorithms, and practical applications. Yet, despite its mathematical sophistication, TDA methodology is surprisingly intuitive and lends itself well to research with students, even at the undergraduate level. The principal lecturer at this conference will be Dr. Vin de Silva who has been a key contributor to the development of TDA. Lecture topics will include winding numbers, simplicial homology and cohomology, the persistence algorithm, stability theorems, zigzag persistence, category theory and generalized persistence, and Reeb cosheaves. In addition to lectures, the conference will feature lab sessions that will offer participants hands-on experience analyzing real data using state-of-the-art TDA software, as well as a poster session highlighting TDA research involving students. This conference will focus on mathematics and computation rather than statistics, and it will emphasize research in the setting of primarily undergraduate institutions.Information about the conference is available at http://pages.stolaf.edu/tda-conference/