Yao Xie

Full publication list can be found here.

Change-point detection

change-point Change-point detection is a fundamental problem in statistics and signal processing for applications such as threat detection and real-time monitoring. Given a sequence of high-dimensional observations, there can be a change-point in space and time, which alters the underlying distribution of the data. One would like to detect such a change as quickly as possible after it occurs.

I am interested in various change detection problems arising from modern applications, and aim to develop novel change-point detection methods that are computationally efficient, statistical powerful, as well as understand the fundamental limits, using techniques from statistics, optimization, and information theory.

Selected Publications

Structured signal processing

change-pointSparsity, low-rank, manifoldal and graphical structures are common geometric features of high-dimensional data. My interests are to develop efficient statistical methods that can exploit these structures to achieve more efficient signal estimation and detection algorithms, characterize their theoretical performance, and understand fundamental limits.

Selected Publications

Network data analysis

change-point Network is a fundamental model for interdependence between variables or physical quantities. Streaming data over networks have become ubiquitous nowadays, arising from sensors networks, social networks, power networks, internet-of-things and smart cities. My interest lies develop statistical framework for online learning and real-time inference of the network structures from noisy and incomplete observations.

Selected Publications

Overview of my research prior to 2013: slides.