Publications

Google scholar

• Huang, H., Hammerling, D., Li, B., and Smith R., Combining Multiple Interdependent Climate Models: A Bayesian Approach. [arXiv]

• Huang, H., Blake, L. R., Katzfuss, M., Hammerling, D. M. (2024+) Nonstationary Spatial Modeling of Massive Global Satellite Data, under review. [arXiv]

• Huang, H., Genton, M. G., and Sun, Y. (2023), Test and Visualization of Covariance Properties for Multivariate Spatio-Temporal Random Fields, Journal of Computational and Graphical Statistics 32(4), 1545-1555. [arXiv]

• Huang, H., Castruccio, S., Baker, A. H., and Genton M. G. (2023) Saving storage in climate ensembles: A model-based stochastic approach (with discussion), Journal of Agricultural, Biological, and Environmental Statistics 28(2), 324-344.

• Huang, H., Castruccio, S., and Genton, M. G.(2022), Forecasting High-Frequency Spatio-Temporal Wind Power with Dimensionally Reduced Echo State Networks, Journal of the Royal Statistical Society Series C (Applied Statistics) 71(2), 449-466. [arXiv]

• Huang, H., Abdulah, S., Sun, Y., Ltaief, H., Keyes, D. E., and Genton, M. G. (2021), Competition on spatial statistics for large datasets (with discussion), Journal of Agricultural, Biological, and Environmental Statistics 26(4), 580-595. [KAUST Discovery Highlight][More info about the competition]

• Blake, L., Huang H., Vanderwende B., Hammerling D. (2021), The Deep-Tree Approach: An Improved Parallel Matlab Implementation of the Multi-resolution Approximation for Massive Spatial Data on High-Performance Computing Systems, NCAR Technical Note (NCAR/TN-565-STR).

• Salvana, M. L., Abdulah, S., Huang, H., Ltaief, H., Sun, Y., Genton, M. G., and Keyes, D. E. (2021), High performance multivariate geospatial statistics on manycore systems, IEEE Transactions on Parallel and Distributed Systems 32, 2719-2733. [arXiv]

• Blake, L., Huang, H., Vanderwende, B., and Hammerling, D. (2019), A Shallow-Tree Multi-resolution Approximation for Distributed and High-Performance Computing Systems, NCAR Technical Note (NCAR/TN-559+STR).

• Huang, H., Blake, L., and Hammerling, D. (2019), Pushing the Limit: A Hybrid Parallel Implementation of the Multi-resolution Approximation for Massive Data, NCAR Technical Note (NCAR/TN-558-STR).

• Huang, H. and Sun, Y. (2019), A Decomposition of Total Variation Depth for Understanding Functional Outliers, Technometrics 61(4), 445-458. [arXiv]

• Huang, H. and Sun, Y. (2018), Hierarchical low rank approximation of likelihoods for large spatial datasets, Journal of Computational and Graphical Statistics 27(1), 110-118. [arXiv][KAUST Discovery Highlight]

• Huang H. and Sun Y. (2017), Visualization and assessment of spatio-temporal covariance properties, Spatial Statistics 34, 100272, [arXiv][KAUST Discovery Highlight]

• Toye, H., Zhan, P., Gapalakrishnan, G., Kartadikaria, R. A., Huang, H., Knio, O., and Hoteit, I. (2017), Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing, Ocean Dynamics, 67(7), 915-933.