Abstract: Evolutionary relationships are represented by phylogenetic trees, and a phylogenetic analysis of gene sequences typically produces a collection of these trees, one for each gene in the analysis. Analysis of samples of trees is difficult due to the multidimensionality of the space of possible trees. In Euclidean spaces, principal component analysis is a popular method of reducing high-dimensional data to a low-dimensional representation that preserves much of the sample's structure. However, the space of all phylogenetic trees on a fixed set of species does not form a Euclidean vector space, and methods adapted to tree-space are needed. In this talk, we introduce recent progress on this open problem.

Bio：唐晓弦2014年毕业于北京大学数学科学学院并取得博士学位。其后，她先后在韩国国家数学研究所，德国不来梅大学以及美国德州农工大学从事博士后研究， 并于2019年获得北京航空航天大学卓越百人特别副研究员职位。主要研究方向是符号计算，研究兴趣为计算代数几何在生物与统计中的应用。