Peer-reviewed publications

1. Murphy, E., Huang, W. K., Bessac, J., Wang, J. and Kotamarthi, R. (2025) Joint Modeling of Wind Speed and Wind Direction Through a Conditional Approach. Environmetrics, 36:e70011. Journal: Bibtex:
2. Russell, B.T., Ding, Y., Huang, W. K., and Dyer, J.L. (2024) Characterizing Asymptotic Dependence between a Satellite Precipitation Product and Station Data in the Northern US Rocky Mountains via the Tail Dependence Regression Framework With a Gibbs Posterior Inference Approach. Environmetrics, 35:e2890. Journal: Bibtex:
3. Li, J., Russell, B. T., Huang, W. K., and Porter, W. C. (2024) Modeling nonstationary surface-level ozone extremes through the lens of US air quality standards: A Bayesian hierarchical approach. Environmetrics, 35:e2882. Journal: Bibtex:
4. Chung, YM, Huang, W. K., Wu, HT. (2024) Topological Data Analysis Assisted Automated Sleep Stage Scoring Using Airflow Signals. Biomedical Signal Processing & Control 89:105760. Journal: Bibtex:
5. Parris, S., Huang, W. K., Jones, D., Bridges, W., Olvey, J., Olvey, M., Saski, C. (2023) Geostatistical techniques to account for the heterogeneity of Fusarium wilt inoculum distribution in upland cotton field screening studies. Crop Science 63(3), 1316-1329. Journal: Bibtex:
6. Wu, Q., Bessac, J., Huang, W. K., Wang, J., Kotamarthi, R. (2022). A conditional approach for joint estimation of wind speed and direction under future climates. Advances in Statistical Climatology, Meteorology and Oceanography, 8(2), 205-224.
7. Wu, H, Tan, X., Zhang, Q., Huang, W. K., Lu, X., Nishimura, Y., Zhang, Y. Multiresolution data assimilation for auroral energy flux and mean energy using DMSP SSUSI, THEMIS ASI, and an empirical model. Space Weather (2022): 20, e2022SW003146.
8. Yaddanapudi, R., Mishra, A., Huang W. K., Chowdhary, H. Compound Wind and Precipitation Extremes in Global Coastal Regions under Climate Change. Geophysical Research Letters (2022): e2022GL098974
9. Huang, W. K. Chung, YM, Wang, YB, Mandel J. E., Wu, HT (2021) Airflow recovery from thoracic and abdominal movements using Synchrosqueezing Transform and Locally Stationary Gaussian Process Regression. Computational Statistics & Data Analysis, 107384. Journal: Bibtex:
10. Huang, W. K. Monahan , A. H., Zwiers, F. W. (2021) Estimating Concurrent Climate Extremes: A Conditional Approach. Weather and Climate Extremes, p. 100332. Journal: arXiv: Bibtex:
11. Russell, B. T. and Huang, W. K. (2021) Modeling short-ranged dependence in block extrema with application to polar temperature data. Environmetrics, 32(3):e2661. Paper: Bibtex:
12. Huang, W.K., Cooley, D. S., Ebert-Uphoff, I., Chen, C., Chatterjee, S. (2019) New Exploratory Tools for Extremal Dependence: Chi Networks and Annual Extremal Networks. Journal of Agricultural, Biological, and Environmental Statistics, Special Issue on Climate and Earth System, 24(3), 484-501. Preprint: Bibtex:
13. Huang, W.K., Nychka, D.W., Zhang, H. (2019) Estimating precipitation extremes using the log-histospline. Environmetrics, Special Issue on Statistics for Climate Informatics, 30(4), e2543. arXiv: Bibtex:
14. Huang, W. K., Stein, M. L., McInerney, D. J., Sun., S., Moyer, E. J. (2016) Estimating changes in temperature extremes from millennial scale climate simulations using generalized extreme value (GEV) distributions. Advances in Statistical Climatology, Meteorology and Oceanography , 2, 79--103, 2016. Paper: Bibtex:
15. Wang J., Han, Y., Stein, M.L, Kotamarthi, R., Huang W. K. , Evaluation of dynamically downscaled extreme temperature using a spatially-aggregated generalized extreme value (GEV) model. Climate Dynamics, 47(9), 2833-2849, 2016. Bibtex:
16. Dixon Hamil, K., Iannone III, B. V., Huang, W. K., Fei, S., and Zhang, H. (2016) Cross-scale contradictions in ecological relationships. Landscape Ecology, 31(1), 7-18. Bibtex:
17. Iannone III, B. V., Potter, K. M., Dixon Hamil, K., Huang, W., Zhang, H., Guo, Q., Oswalt, C. M., Woodall, C. W., and Fei, S. (2016) Evidence of biotic resistance to invasions in forests of the Eastern USA. , Landscape Ecology, 31(1), 85-99. Bibtex:

Refereed White Papers and Conference Proceedings

1. Feng, Y., Maulik, R., Wnag, J., Balaprakash, P., Huang, W. K., Rao, Vishwas, Xue, P., Pringle, W., Bessac, J., and Sullivan, R. Characterization of extremes and compound impacts: Applications of machine learning and interpretable neural networks, Artificial Intelligence for Earth System Predictability (AI4ESP) Collaboration, United States, 2021. Bibtex:
2. Ebert-Uphoff, I., Huang, W.K., Mitra, A., Cooley, D.S., Chatterjee, S.B., Chen, C., and Wang, Z. (2018) Studying extremal dependence in climate using complex networks. Proceedings of the 8th International Workshop on Climate Informatics (CI 2018), Boulder, CO. Bibtex:
3. Malik, A., Maciejewski, R., Elmqvist, N., Jang, Y., Ebert, D. S., and Huang, W. (2012) A correlative analysis process in a visual analytics environment. Visual Analytics Science and Technology (VAST), 2012 IEEE Conference on, 33-42, 2012. Bibtex:

Non-refereed publications

1. Huang, W.K., "Statistics of Extremes with Applications in Climate". PhD thesis, Purdue University, 2017. Bibtex: