Research

Convention: * for co-first authors.

1. SLOPE and its role in design for generalization.
   Miao, X., Zhao, J., Kang, H., 2024. Under preparation.
   [30-min slides at ACIC]
2. Transfer learning between U.S. presidential elections: how should we learn from a 2020 ad campaign to inform 2024 ad campaigns?
   Miao, X., Zhao, J., Kang, H., 2024. Under review.
   [arXiv] [15-min slides at NESS] [75-min slides at MEAD]
3. Assumption-lean and data-adaptive post-prediction inference.
   Miao, J., Miao, X., Wu, Y., Zhao, J., and Lu, Q, 2024+. Under revision.
   [arXiv]
4. multimedia: multimodal mediation analysis of microbiome data.
   Jiang, H.*, Miao, X.*, Thairu, M., Beebe, M., Grupe, D., Davidson, R.J., Handelsman, J., Sankaran, K., 2025. Microbiology Spectrum, 13(2), e01131-24.
   [biorXiv] [Microbiology Spectrum]
5. Valid inference for machine learning-assisted GWAS.
   Miao, J., Wu, Y., Sun, Z., Miao, X., Lu, T., Zhao, J., and Lu, Q., 2024. Nature Genetics, 56(11), 2361-2369.
   [Nature Genetics]
6. Sample size formula for general win ratio analysis.
   Mao, L., Kim, K. and Miao, X., 2022. Biometrics, 78(3), pp.1257-1268.
   [Biometrics]
7. Interactive visualization and representation analysis applied to glacier segmentation.
   Zheng, M., Miao, X. and Sankaran, K., 2022. ISPRS International Journal of Geo-Information, 11(8), p.415.
   [ISPRS International Journal of Geo-Information]
8. Multicenter reproducibility of liver iron quantification with 1.5-T and 3.0-T MRI.
   Hernando, D., Zhao, R., Yuan, Q., Aliyari Ghasabeh, M., Ruschke, S., Miao, X., Karampinos, D.C., Mao, L., Harris, D.T., Mattison, R.J. and Jeng, M.R., Pedrosa, I., Kamel, I.R., Vasanawala, S., Yokoo, T. and Reeder, S.B., 2022. Radiology.
   [Radiology]

Presentations

1. SLOPE And Its Role In Design For Generalization (and earlier versions) [30-min slides at ACIC]
• American Causal Inference Conference (ACIC) , Detroit, Michigan, May 16, 2025.
• Joint Statistical Meetings (JSM), Portland, Oregon, August 6, 2024.
• Eastern North American Region (ENAR), Baltimore, March 13, 2024.
2. Transfer Learning Between U.S. Presidential Elections: How Should We Learn From A 2020 Ad Campaign To Inform 2024 Ad Campaigns? [arXiv] [15-min slides at NESS] [75-min slides at MEAD]
• Joint Statistical Meetings (JSM), Nashvile, Tennessee, August 5, 2025.
• New England Statistics Symposium (NESS), New Haven, Connecticut, June 2, 2025.
• Models, Experiments, and Data Workshop (MEAD), Madison, Wisconsin, February 14, 2025.
• American Causal Inference Conference (ACIC) , Seattle, Washington, May 15, 2024.
• UW-Madison Statistics Graduate Association Seminar, Madison, Wisconsin, April 29, 2024.