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Publications and Preprints


(Note:     students under my supervision;  * corresponding author)

  • An ODE model for dynamic matching in heterogeneous networks. [pdf][code]

Xiaowu Dai* and Hengzhi He.

Preprint, 2023+.

  • Robust multi-item auction design using statistical learning: Overcoming uncertainty in bidders' types distributions. [pdf][code]

Jiale Han and Xiaowu Dai*. 

Preprint, 2023+.

  • Double matching under complementary preferences. [pdf][code]

Yuantong Li, Guang Cheng, and Xiaowu Dai*.

Preprint, 2023+.

  • Incentive-aware recommender systems in two-sided markets. [pdf]

Xiaowu Dai, Yuan Qi, and Michael Jordan.  

Preprint, 2022+.

  • Post-regularization confidence bands for ordinary differential equations. [pdf]

Xiaowu Dai and Lexin Li. 

Preprint, 2022+; Under Revisions at Journal of Machine Learning Research.

  • Nonparametric estimation via mixed gradients. [pdf]

Xiaowu Dai.

Preprint, 2022+; Under Revisions at Journal of the Royal Statistical Society: Series B.

  • A resampling approach for causal inference on novel two-point time-series with application to identify risk factors for type-2 diabetes and cardiovascular disease. [pdf]

Xiaowu Dai, Saad Mouti, Marjorie Lima do Vale, Sumantra Ray, Jeffrey Bohn, and Lisa Goldberg. 

Preprint, 2022+; Under Revisions at Statistics in Biosciences.

  • Another look at statistical calibration: A non-asymptotic theory and prediction-oriented optimality. [pdf]

Xiaowu Dai and Peter Chien. 

Preprint, 2022+.

  • Selection and estimation optimality in high dimensions with the TWIN penalty. [pdf]

Xiaowu Dai and Jared Huling.

Preprint, 2022+.


Xiaowu Dai, Xiang Lyu, and Lexin Li.

Journal of the American Statistical Association: Theory and Methods (JASA), 2022.

  • Orthogonalized kernel debiased machine learning for multimodal data analysis. [journal][preprint]

Xiaowu Dai and Lexin Li.

Journal of the American Statistical Association: Theory and Methods (JASA), 2021.

  • Learning strategies in decentralized matching markets under uncertain preferences. [journal][preprint]

Xiaowu Dai and Michael Jordan.

Journal of Machine Learning Research (JMLR), 2021.

Xiaowu Dai and Michael Jordan.

Advances in Neural Information Processing Systems (NeurIPS), 2021.

Xiaowu Dai and Lexin Li.

Journal of the American Statistical Association: Theory and Methods (JASA), 2021.

  • A synthesis of pathways linking diet, metabolic risk and cardiovascular disease: A framework to guide further research and approaches to evidence-based practice. [journal][pubmed]

Marjorie Lima do Vale, Luke Buckner, Claudia-Gabriela Mitrofan, Kai Sento Kargbo, Rajna Golubic, Ali Ahsan Khalid, Sammyia Ashraf, Saad Mouti, Xiaowu Dai, David Unwin, Jeffrey Bohn, Lisa Goldberg, and Sumantra Ray.​ 

Nutrition Research Reviews (NRR), 2021.

Xiaowu Dai and Yuhua Zhu.

Journal of Statistical Theory and Practice (JSTP), special issue on "Advances in Deep Learning", 2020. 

  • High-dimensional smoothing splines and application in Alzheimer's disease prediction using magnetic resonance imaging. [journal][preprint]

Xiaowu Dai.

Statistics in Biopharmaceutical Research (SBR), 2019.

  • High-dimensional varying coefficient models for Alzheimer's disease diagnosis with longitudinal and heterogeneous structural MR images. [journal]

Xiaowu Dai.

Alzheimer's & Dementia (AD), 2018.


  • Statistical learning-aided design for a blockchain payment system. [pdf]

Xiaowu Dai. 

Research Vignette, Simons Institute for the Theory of Computing, 2020.

  • Statistical machine learning for complex data sets. [pdf]

Xiaowu Dai. 

Ph.D. Thesis, Department of Statistics, UW-Madison, 2019.

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