The Division of Mathematical Sciences (DMS) at the National Science Foundations (NSF) has awarded Yen-Chi Chen, Assistant Professor of Statistics, a CAREER award for his research on “Inference with Graphs: Density Skeleton and Markov Missing Graph”. This is NSF’s most prestigious award. It is presented once a year in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.

Chen’s research project introduces novel frameworks of using graphs in analyzing a complex dataset. These new applications of graphs allow us to investigate the intricate relation among quantities of interest.  Also, this research will design novel methodologies to handle complex missing data problems in the National Alzheimer's Coordinating Center's database. This project highlights how abstract mathematical objects like graphs offer a unified treatment on problems arising from different fields such as Astronomy and dementia studies. The project will provide training for graduate students and opportunities for involving undergraduate students in research.

This project will help initiate three new education programs: designing R shiny apps to illustrate statistical theory, developing a new course covering learning theory at the undergraduate level, and facilitating the directed reading program at UW. The new statistical learning course will complement existing methodology-focused statistical learning courses offered in many universities by providing a theoretical introduction of the contents at the undergraduate level. All materials developed from this new course will be shared with the public and the contents will be presented in statistical education conferences such as the United States Conference on Teaching Statistics. This project will also engage both the graduate and undergraduate students in research in various ways, such as participating in the Washington Experimental Mathematics Lab and the Washington Directed Reading Program.