Peer-reviewed
[1] Song, D., Lewis, W., Knapp, P.F., Wu, C.F.J., Joseph, V.R. (2025). Efficient Optimization of Plasma Radiation Detector Configurations using Imperfect Inference Models. Journal of the American Statistical Association, 1–16. link
[2] Song, D., and Joseph, V. R. (2025). Efficient Active Learning Strategies for Computer Experiments. Technometrics, 1–14. link
[3] Song, D., He, L., Li, W., and Yang, M. (2024). A Systematic View of Information-based Optimal Subdata Selection: Algorithm Development, Performance Evaluation, and Application in Financial Data. Statistica Sinica, 34, 611-636. link
[4] Song, D., Mak, S., and Wu, C.F.J. (2023). ACE: Active Learning for Causal Inference with Expensive Experiments. In KDD Workshop 2023: Causal Inference and Machine Learning in Practice: Use cases for Product, Brand, Policy, and beyond. arxiv
Submitted
[5] Song, D., and Joseph, V. R. (2025+). Efficient Screening Designs for Expensive Black-box Models with Qualitative and Quantitative Factors. Under review at Journal of the American Statistical Association. Manuscript available upon request.
Preprint
[6] Li, X., Song, D., Han, M., Zhang, Y., and Kizilcec, R. F. (2021). On the limits of algorithmic prediction across the globe. arxiv