The project aims to provide a systematic solution to the difficult problem of change-point detection under irregular signals. Unlike the traditional setting in which signals before and after the change point are often assumed to differ by a constant shift, irregular signals refer to the situation when the post-change signal may vary in highly unpredictable ways without any pre-specifiable pattern or structure. This can pose a tremendous challenge on many existing change-point tests, often resulting in notable reductions in their statistical power and increasing their vulnerability to maliciously designed adversarial attacks. By allowing the post-change signals to be irregular and not necessarily follow the standard assumptions as in conventional change-point analyses, the team of Ting Zhang (Lead PI, Professor in Statistics, University of Georgia), Wei Biao Wu (Professor in Statistics, The University of Chicago) and Maggie Cheng (Professor in Applied Mathematics and Director of the Center for Interdisciplinary Scientific Computation, Illinois Institute of Technology) expect to develop more robust and next-generation statistical protocols and toolboxes with rigorous theoretical guarantees for change-point detection in a wide range of applications. For example, detecting abrupt changes in power grids, attacks in sensor networks, or emerging trends in social networks all require powerful methods for detecting irregular changes. As a result, the research will advance not only the field of statistics but also a range of other disciplines where data with irregular signals may arise. 

 

Dr. Zhang recently reflected on the importance of this award, his first collaborative project to receive external funding: "Although I have been fortunate to receive consistent support from NSF, including the prestigious NSF CAREER Award, this grant holds special significance for me as my first non-sole-PI award. It represents an important step in my own research journey, allowing me to experience firsthand and enjoy the benefits of collaboration and the collective expertise that a team can bring to addressing complex scientific problems that are beyond the reach of any single investigator."

 

Congratulations, Ting, on this outstanding achievement!