Lijia Wang holds a Bachelor's degree in Mathematics from the University of California Irvine and earned a Master's degree in Statistics and a Ph.D. in Applied Mathematics from the University of Southern California, both within the Mathematics Department. Her research focuses on statistical network modeling and asymmetric error control, spanning topics like local community detection, social network analysis, optimal testing procedures, confidence intervals and Naymen-Person classification.
Journal
- Wang, Lijia. , Wang, Y.X. Rachel. , Li, Jingyi. Jessica. & Tong, Xin. (2023). Hierarchical Neyman-Pearson Classification for Prioritizing Severe Disease Categories in COVID-19 Patient Data. Journal of the American Statistical Association. forthcoming .
- Bartroff, Jay. , Lorden, Gary. & Wang, Lijia. (2023). Optimal and fast confidence intervals for hypergeometric successes. The American Statistician. 77(2), 151-159.
- Wang, Lijia. , Han, Xu. & Tong, Xin. (2022). Skilled mutual fund selection: false discovery control under dependence. Journal of Business & Economic Statistics. 41(2), 1-15.
- Wang, Lijia. , Tong, Xin. & Wang, Y.X. Rachel. (2022). Statistics in everyone’s backyard: An impact study via citation network analysis. Patterns. 3(8), 100532.
- Interiano, Myra. , Kazemi, Kamyar. , Wang, Lijia. , Yang, Jienian. , Yu, Zhaoxia. & Komarova, Natalia. L. (2018). Musical trends and predictability of success in contemporary songs in and out of the top charts. Royal Society open science. 5(5), 171274.
Openings
- I am looking for highly motivated Ph.D. students with a background in statistics, mathematics, or related fields. If you are interested, please send your CV and transcript(s) to lijiwang@cityu.edu.hk. I look forward to receiving your application.
Last update date :
15 Jan 2024
