Papers (see also Google Scholar)

* = equal contributions

SLOPE and designing robust studies for generalization. Under Review.
Miao, X., Zhao, J., Kang, H. (2025+).

Transfer learning between U.S. presidential elections: how should we learn from a 2020 ad campaign to inform 2024 ad campaigns?. Under Revision.
Miao, X., Zhao, J., Kang, H. (2025+).

Assumption-lean and data-adaptive post-prediction inference. Journal of Machine Learning Research.
Miao, J.*, Miao, X.*, Wu, Y., Zhao, J., and Lu, Q, 2025.

multimedia: multimodal mediation analysis of microbiome data. Microbiology Spectrum, 13(2), e01131-24.
Jiang, H.*, Miao, X.*, Thairu, M., Beebe, M., Grupe, D., Davidson, R.J., Handelsman, J., Sankaran, K. (2025).

Valid inference for machine learning-assisted GWAS. Nature Genetics, 56(11), 2361–2369.
Miao, J., Wu, Y., Sun, Z., Miao, X., Lu, T., Zhao, J., and Lu, Q. (2024).

Sample size formula for general win ratio analysis. Biometrics, 78(3), 1257–1268.
Mao, L., Kim, K., and Miao, X. (2022).

Interactive visualization and representation analysis applied to glacier segmentation. ISPRS International Journal of Geo-Information, 11(8), 415.
Zheng, M., Miao, X., and Sankaran, K. (2022).

Multicenter reproducibility of liver iron quantification with 1.5-T and 3.0-T MRI. Radiology.
Hernando, D., Zhao, R., Yuan, Q., Aliyari Ghasabeh, M., Ruschke, S., Miao, X., Karampinos, D.C., Mao, L., Harris, D.T., Mattison, R.J., Jeng, M.R., Pedrosa, I., Kamel, I.R., Vasanawala, S., Yokoo, T., and Reeder, S.B. (2022).