Publications

Spatial Methodology

  1. Zhan, W., & Katzfuss, M. (2026+). Tensor Covariance Estimation via Kronecker-Structured Sparse Inverse Cholesky. ArXiv Preprint ArXiv:2608.14887 (Submitted).
  2. Zhan, W., & Datta, A. (2025). Neural networks for geospatial data. Journal of the American Statistical Association, 120(549), 535–547.
  3. Zhan, W., & Datta, A. (2026). geospaNN: A Python package for geospatial neural networks. Journal of Open Source Software, 11(117), 8389.

Manuscript in preparation

  1. Zhan, W., & Datta, A. (2026+). Deep Neural Networks for Estimation under Spatial Confounding. In Preparation.
  2. Zhan, W., & Katzfuss, M. (2026+). Latent tensor modeling via Kronecker-structured sparse inverse Cholesky. In Preparation.
  3. Zhan, W., Brachem, J., Wright, D., & Katzfuss, M. (2026+). Distributional calibration of multi-fidelity climate models with sparse observations: An application to stochastic wind event sets. In Preparation.

Collaboration

  1. Jackson, C., Cherry, C., ... Zhan, W. ..., & others. (2025). Distinct myeloid-derived suppressor cell populations in human glioblastoma. Science, 387(6731), eabm5214.
  2. Dykema, A. G., Zhang, J., ... Zhan, W. ..., & others. (2023). Lung tumor–infiltrating Treg have divergent transcriptional profiles and function linked to checkpoint blockade response. Science Immunology, 8(87), eadg1487.
  3. Zeng, Z., Connor, S., Zhang, J., Zhan, W., Ji, H., Pardoll, D., & Smith, K. N. (2023). A minimal gene set to overcome phenotypic heterogeneity in characterization of neoantigen-specific TIL in lung cancer. Journal for ImmunoTherapy of Cancer, 11(Suppl 1), A1146.