搜索:
 
 当前位置:>首页 -> 学术报告
7-18天元基金几何与随机分析及其应用交叉讲座之67【吴畏】

报告题目:Phase Variability in Functional Data and its Applications

报告人:吴畏

报告时间:7月18日 4:00-5:00

报告地点:1318

In this talk, I will present my research on function registration and its applications over the past few years.  Focusing on statistical modeling for functional data, we have recently developed a novel geometric framework to compare, align, average, and model a collection of random functional observations, where the key step is to find an optimal time warping between two functions for a feature-to-feature alignment.  This framework is based on extending the nonparametric version of the Fisher-Rao Riemannian metric to general function spaces, and relies on the fact that this metric is invariant to identical warpings of its arguments. The theoretical underpinning of this new method is established by proving the consistency under a semi-parametric model.  We demonstrate this new framework using experimental data in various application domains such as ECG bio-signals, proteomics data, 3D protein structures.  Finally, I will present the latest research problems we are working on under the new registration framework. 

个人简介:

Dr. Wei Wu is an Associate Professor in the Department of Statistics at the Florida State University.  He received the B.S. degree in Applied Mathematics from USTC in 1998 and the PhD degree in Applied Mathematics from Brown University in 2004.  His research interests include Computational Statistics, Machine Learning, Functional Data Analysis, Point Process Models, and Shape Analysis.  He is also interested in interdisciplinary applications in neuroscience and bioinformatics.


  科大主页 | 国家数学与交叉科学中心(合肥) | 中科院吴文俊数学重点实验室 |
中科院数学与系统科学研究院 | 北京国际数学研究中心 | 安徽省数学会