Haeun Moon

About

I am an assistant professor in the School of Transdisciplinary Innovations and the Department of Statistics at Seoul National University.

Before joining SNU, I was a postdoctoral researcher in the Department of Statistics and Data Science at Carnegie Mellon University, mentored by Dr. Kathryn Roeder and Dr. Jing Lei. I was also involved in several genetic projects mentored by Dr. Bernie Devlin. I received my Ph.D. in 2022 from the Department of Statistics at the University of Pittsburgh, advised by Dr. Kehui Chen. Before joining a Ph.D. program, I worked as an economic statistician at the Bank of Korea for 2.5 years. I obtained a M.A. in Economics from Seoul National University and a B.S. in Mathematical Science from KAIST.

Research Interest 

My research focuses on making inferences about data with minimal assumptions. This involves exploring measures of dependence, conditional dependence, and variable importance in general. I also consider which other measures can be derived from a nonparametric framework to provide deeper insights into the data. I explore how to incorporate black-box prediction algorithms into a pipeline in a statistically principled way. These areas of study naturally align with topics of variable selection and multiple testing. Recently, I have been considering the use of predictive inference techniques for both methodological innovation and practical applications. 

Here is my CV (update: 2024.9.1).

Employment

• Assistant Professor, Seoul National University (2024.9-present)

Joint affiliation at the School of Transdisciplinary Innovations and the Department of Statistics

• Postdoctoral Researcher, Institute for Data Innovation in Science, Seoul National University (2024.6-2024.8)

• Postdoctoral Researcher,  Department of Statistics and Data Science, Carnegie Mellon University (2022.7-2024.5)

• Economic Statistician, the Bank of Korea (2015.1-2017.7)