Title:  Point Process-based Modeling and Analysis of Asynchronous Event Sequences

Committee:

Dr. Hongyuan Zha, CoC, Advisor, Chair , Advisor

Dr. Mark Davenport, ECE, Co-Advisor

Dr. Justin Romberg, ECE

Dr. Le Song, CoC

Dr. Chuanyi Ji, ECE

Dr. Bistra Dilkina, CSE

Abstract:

Real-world interactions among multiple entities, such as user behaviors in social networks, job hunting and hopping, and diseases and their complications, often exhibit self-triggering and mutually-triggering patterns. For example, a tweet of a twitter user may trigger further responses from her friends. A disease of a patient may trigger other complications. Temporal point processes, especially Hawkes processes and correcting processes, have a capability to capture the triggering patterns quantitatively. This talk aims to introducing basic concepts of point processes and proposing a series of cutting-edge techniques for practical applications. In particular, the Granger causality analysis of Hawkes processes, the clustering problem of event sequences, the combination of deep learning and point processes, and some interesting applications will be discussed.