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• Jin, L. and Li, B., Scalable methods for multiple time series comparison (2024), Technometrics, to appear.
• Tonks, A.*, Harris, T., Li, B., Brown, B., Smith, R., Forecasting West Nile virus with graph neural networks: Harnessing spatial dependence in irregularly sampled geospatial data (2024), GeoHealth, to appear.
• Campos, M.*, Li, B., de Lafontaine, G., Napier, J., Hu, F.S., Integrating different data sources using a Bayesian hierarchical model to Unveil Glacial Refugia (2023), Journal of Agricultural, Biological and Environmental Statistics, to appear.
• Chen, F., Hou, Z., Saarela, S., McRoberts, R. E., St\.ahl, G., Kangas, A., Packalen, P., Li, B., and Xu, Q., Leveraging remotely sensed non-wall-to-wall data for upscaling in forest inventory (2023), International Journal of Applied Earth Observation and Geoinformation, to appear.
• Harris, T., Li, B., Sriver, R., Multi-model Ensemble Analysis with Neural Network Gaussian Processes (2023), Annals of Applied Statistics, 17(4), 3403-3425.
• Qu, T.*, Li, B., Chan, S. and Albraccine, D., Bias correction for nonignorable missing counts of areal HIV new diagnosis (2023), STAT, to appear.
• Xu, Q., Li, B., McRoberts, R. E., Li, Z. and Hou, Z., Harnessing data assimilation and spatial autocorrelation for forest inventory (2023), Remote Sensing of Environment, 288, 1-13.
• Li, B. and Simpson, D., Reflections on IDEA Forum – Statistics, Climate Change and Sustainability (2023), Chance, 36, 25-30.
• Wang, M.*, Harris, T. and Li, B., Asynchronous changepoint estimation for spatially correlated functional time series (2023), Journal of Agricultural, Biological and Environmental Statistics, 28, 157-176.
• Park, Y., Li, B., Li, Y., Crop yield prediction using Bayesian spatially varying coefficient models with functional predictors (2023), Journal of the American Statistical Association, 118, 70-83.
• Hou, Z., McRoberts, R., Zhang, C., Zhao, X., Wang, X., Li, B., Xu, Q. Cross-Classes Domain Inference with Network Sampling for Natural Resource Inventory (2022), Forest Ecosystems, 9, 100029, 1-12.
• Li, B. and Shand, L., Discussion for “Bayesian Nonstationary and Nonparametric Covariance Estimation for Large Spatial Data” by Kidd and Katzfuss (2022), Bayesian Analysis, 17, 313-317.
• Sass, D.*, Li, B., Clifton, M., Harbison, J., Xamplas, and Smith, R., The impact of adulticide on Culex abundance and infection rate in the North Shore of Cook County, Illinois (2021), Journal of the American Mosquito Control Association, 38, 46-58.
• Yun, S.*, Smerdon, J., Li, B. and Zhang, X., A pseudoproxy assessment of why climate field reconstruction methods perform the way they do in time and space (2021), Climate of the Past, 17, 2583-2605.
• Harris, T.*, Li, B., Tucker, D., Scalable multiple changepoint detection for functional data sequences (2021), Environmetrics, 33, e2710.
• Yun, S.*, Zhang, X.**, Li, B., Detection of local differences in spatial characteristics between two spatiotemporal random fields (2022), Journal of the American Statistical Association, 117, 291-306.
• Zhou, W., Guan, K., Peng, B., Wang, Z., Fu, R., Li, B., Ainsworth, E. A., DeLucia, E., Zhao, L., and Chen, Z., A generic risk assessment framework to evaluate historical and future climate-induced risk for rainfed corn and soybean yield in the U.S. Midwest (2021), Weather and Climate Extremes, 33:100369.
• Sass, D.*, Farkhad, B.*, Li, B., Chan, M. and Albarracin, D., Are spatial models ad- vantageous for predicting county level HIV epidemiology across the United States? (2021) Spatial and Spatio-temporal Epidemiology, 38:100436.
• Sass, D.*, Li, B. and Reich, B., Flexible and fast spatial extremes model with fused penalty (2021), Journal of Computational Graphical Statistics, 30, 1124-1142.
• Uelmen, J. A., Irwin, P., Brown, W. M., Karki, S., Ruiz, M. O., Li, B. and Smith, R., Assessing ultra-fine-scale factors to improve human West Nile virus disease models in the Chicago area, USA (2021), PLOS ONE, 16(5):e0251517.
• Miller, D., Wang, Z., Li, B., Harnos, D. S. and Ford, T., Skillful Subseasonal prediction of United States extreme warm days and standardized precipitation index in Boreal summer (2021), Journal of Climate, to appear.
• Xu, Q., Stahl, G., McRoberts, R., Li, B., Tokola, T., Hou, Z., Generalizing systematic adaptive cluster sampling for forest ecosystem inventory (2021), Forest Ecology and Management, 489, 119051, 1-10.
• Jiang, H., Hu, H., Li, B., Zhang, Z., Wang, S. and Lin, T., Understanding the non-stationary relationships between corn yields and meteorology via a spatiotemporally varying coefficient model (2021), Agricultural and Forest Meteorology, 301, 108340, 1-12.
• Uelmen, J. A., Irwin, P., Bartlett, D., Brown, W. M., Karki, S., Ruiz, M. O., Fratterigo, J., Li, B. and Smith, R., Effects of Scale on Modeling West Nile Virus Disease Risk (2020), American Journal of Tropical Medicine & Hygiene, 104, 151-165
• Harris, T.*, Li, B., Steiger, N., Smerdon, J., Narisetty, N. and Tucker, D., Evaluating proxy influence in assimilated paleoclimate reconstructions – Testing the exchangeability of two ensembles of spatial processes (2020), Journal of the American Statistical Association, to appear. R package
• Harris, T.*, Tucker, D., Li, B. and Shand, L., Elastic depths for detecting shape anomalies in functional data, (2020), Technometrics, to appear.
• Stone, C., Zuo, Z.*, Li, B., Ruiz, M. O., Swanson, J., Hunt, J., Kim, C. H. and Smith, R. L., Spatial, temporal, and genetic invasion dynamics of Aedes albopictus (Diptera: Culicidae) in Illinois (2020), Journal of Medical Entomology, 57, 1488-1500.
• Barboza, L., Emile-Geay, J., Li, B., He, W., Efficient Reconstructions of Common Era Climate via Integrated Nested Laplace Approximations (2019), Journal of Agricultural, Biological, and Environmental Statistics, 24, 535-554.
• Zhou, K., Zheng, Y., Li, B., Dong, W. and Zhang, X., Forecasting different types of convective weather: A deep learning approach (2019), Journal of Meteorological Research, 33, 797-809.
• Li, Y., Guan, K., Yu, A., Peng, B., Zhao, L., Li, B. and Peng, J., Toward building a transparent statistical model for improving crop yield prediction (2019), Field Crops Research, 234, 55-65.
• Harris, T.* and Li, B., Kriging (2019), Wiley StatsRef-Statistics Reference Online, John Wiley & Sons Ltd. https://onlinelibrary.wiley.com/doi/book/10.1002/9781118445112.
• Xu Q.*, Li, B., Hou, Z., Vauhkonen, J., Maltamo, M. and Tokola, T., DBH prediction using allometry described by bivariate copula distribution (2019), Forest Ecology and Management, 434, 205-212.
• Cao, Y.* and Li, B., Assessing models for spatial extremes and methods for uncertainty quantification on return level estimation (2019), Environmetrics, 30, 1-21.
• Xu, Q.*, Man, A.*, Fredrickson, M.*, Hou, Z., Pitkanen, J., Wing, B., Ramirez, C., Li, B. and Greenberg, J. Quantification of uncertainty in aboveground biomass estimates derived from small-footprint airborne LiDAR (2018), Remote Sensing of Environment, 216, 514-528.
• Lohmann, S., White, B. X., Zuo, Z.*, Chan, S. M., Morales, A., Li, B., Zhai, C. and Albarracín, D. HIV Messaging on Twitter: An Analysis of Current Practice and Data-Driven Recommendations (2018), AIDS, DOI: 10.1097/QAD.0000000000002018.
• Dasgupta, A. and Li, B., Detection and Analysis of Spikes in a Random Sequence (Appendix) (2018). Methodology and Computing in Applied Probability, 20, 1429-1451.
• Shand, L.*, Li, B., Park, T. and Albraccin, D. Spatially varying auto‐regressive models for prediction of new human immunodeficiency virus diagnoses (2018), Journal of Royal Statistical Society Series C, 67, 1003-1022.
• Craigmile, P., Haran, M., Li, B., Manshardt, E., Rajaratnam, B. and Tingley, M. Paleoclimate reconstruction: looking backwards to look forward (2017), in Handbook of Environmental and Ecological Statistics, A. Gelfand, M. Fuentus, J. Hoeting, and R. Smith (eds), Chapman & Hall, Chapter 33.
• Craigmile, P. and Li, B., Instruments, Proxies, and Simulations: exploring imperfect measures of climate (2017), Chance, 30, 12-18.
• Guan, K., Wu, J., Kimball, J., Anderson, M. C., Frolking, S., Li, B., Hain, C. and Lobell, D. The shared and unique values of optical, ourescence, thermal and microwave satellite data for estimating large-scale crop yields (2017), Remote Sensing of Environment, 199, 333-349.
• Shand, L.*. and Li, B., Modeling Nonstationarity in Space and Time (2017), Biometrics, 73, 759-768.
• Zheng, Y., Xue, M., Li, B., Chen, J. and Tao, Z., Spatial characteristics of extreme rainfall over China with hourly through 24-hour accumulation periods based on national-level hourly rain gauge data (2016), Advances in Atmospheric Sciences, Vol. 33, 1218-1232.
• Li, B., Barboza, L., Tingley, M. and Viens, F., Discussion on Temperature Reconstruction with Sediment Core Data in Ilvonen et al. (2016), Environmetrics, to appear.
• Li, B., Zhang, X. and Smerdon, J., Comparison between spatio-temporal random processes and application to climate model data (2016), Environmetrics, Vol. 27, 267-279.
• Tingley, M., Craigmile, P., Haran, M., Li, B., Mannshardt, E. and Rajaratnam, B. On discriminating between GCM forcing congurations using Bayesian reconstructions of Late Holocene temperatures (2015), Journal of Climate, Vol. 28, 8264-8281.
• Choi, I.*, Li, B., Zhang, H. and Li, Y. Modeling space-time varying ENSO teleconnections to droughts in North America (2015), STAT, Vol. 4, 140-156.
• Auffhamer, M., Li, B., Wright, B. and Yoo, S. J., Specification and estimation of the transfer function in paleoclimate reconstructions (2015), Environmental and Ecological Statistics, Vol. 22, 105-126.
• Gurney, K., Huang, J., Coltin, K. and Li, B., Second letter to editor in response to author response published in J. Air Waste Manage. Assoc. (2015), Vol. 64, 1218-1220.
• Barboza, L.*, Li, B., Tingely, M. and Viens, F., Reconstructing past climate from natural proxies and estimated climate forcings using short- and long-memory models (2014), Annals of Applied Statistics, Vol. 8, 1966-2001.
• Halfacre, J. W., Knepp, T. N., Shepson, P. B., Thompson, C. R., Pratt, K. A., Li, B., Peterson, P. K., Walsh, S. J., Simpson, W. R., Matrai, P. A., Bottenheim, J. W., Netcheva, S., Perovich, D. K., Richter, A., Temporal and spatial characteristics of ozone depletion events from measurements in the Arctic (2014), Atmospheric Chemistry and Physics, Vol. 14, 4875-4894.
• Zhang, X., Li, B. and Shao, X., A self-normalized approach to inference for spatial data (2014), Scandinavian Journal of Statistics, Vol. 41, 311-324.
• Choi, I.*, Li, B. and Wang, X., Nonparametric estimation of spatial and space-time covariance function (2013), Journal of Agricultural, Biological and Environmental Statistics, Vol. 18, 611-630.
• Li, B. and Genton, M. G., Nonparametric Identification of Copula Structures (2013), Journal of the American Statistical Association, Vol. 108, 666-675.
• Cheng, G., Zhao, Y. and Li, B., Empirical likelihood inferences for the semiparametric additive isotonic regression (2012) Journal of Multivariate Analysis, Vol. 112, 172-182.
• Li, B. and Smerdon, J. E., Defining spatial assessment metrics for evaluation of paleoclimatic field reconstructions of the Common Era (2012) Environmetrics, Vol. 23, 394-406.
• Tingley, M. and Li, B., Comments on “Reconstructing the NH mean temperature: Can underestimation of trends and variability be avoided?” (2012), Journal of Climate, Vol. 25, 3441-3446.
• Gurney, K. R., Castillo, K., Li, B. and Zhang, X., A positive carbon feedback to ENSO and volcanic aerosols in the tropical terrestrial biosphere (2012), Global Biogeochemical Cycles, Vol. 26, GB1029, doi:10.1029/2011GB004129.
• Tingley, M., Craigmile, P., Haran, M., Li, B., Mannshardt-Shamseldin, E. and Rajaratnam, B., Piecing together the past: Statistical insights into paleoclimatic reconstructions (2012), Quaternary Science Reviews, Vol. 35, 1-22.
• Sun, Y., Li, B. and Genton, M. G., Geostatistics for large datasets (2012) in Space-Time Processes and Challenges Related to Environmental Problems,, E. Porcu, J. M. Montero, M. Schlather (eds), Springer, Vol. 207, Chapter 3, 55-77.
• Li, B., Ensemble (2012), in Encyclopedia of Environmetrics, A. H. El-Shaarawi, W. W. Piegorsch (eds), John Wiley and Sons.
• Li, B., Sain, S., Mearns, L. O., Anderson, H. A., Kovats, S., Ebi, K. L., Bekkedal, M. Y. V., Kanarek, M. S. and Patz, J. A., The impact of extreme heat on morbidity in Milwaukee, Wisconsin (2012), Climatic Change, Vol. 110, 959-976.
• Li, B. and Zhang, H., An approach to modeling asymmetric multivariate spatial covariance structure (2011), Journal of Multivariate Analysis, Vol. 102, 1445-1453.
• Nychka, D. W. and Li, B. Discussion to: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperature over the last 1000 years reliable? by McShane and Wyner (2011), Annals of Applied Statistics,Vol. 5, 80-82.
• Li, B. and Genton, M. G., Discussion on the Paper by Lindgren, Rue and Lindstrom, (2011) Journal of the Royal Statistical Society, Series B, Vol. 73, 480-481.
• Li, B., Wang, X., Discussion to “Clustering random curves under spatial interdependence with application to service accessibility” by H. Jiang and N. Serban, (2011) Technometrics, Vol. 54, 127-128.
• Ammann, C. M., Genton, M. G. and Li, B. Correcting for signal attenuation from noisy proxy data in climate reconstruction (2010), Climate of the Past, Vol. 6, 273-279.
• Li, B., Nychka, D. W. and Ammann, C. M. The value of multi-proxy reconstruction of past climate (with discussions and rejoinder) (2010), Journal of the American Statistical Association , Vol. 105, 883-911.
• Shao, X. and Li, B., A tuning parameter free test for properties of space-time covariance functions (2009) Journal of Statistical Planning and Inference, Vol. 139, 4031-4038.
• Lund, R. and Li, B., Revisiting climate region definitions via clustering (2009) Journal of Climate, Vol. 22, 1787-1800.
• Li, B., Murthi, A., Bowman, K., North, G., Genton, M. G., and Sherman, M., Statistical tests of Taylor’s hypothesis: an application to precipitation fields (2009) Journal of Hydrometeorology, Vol. 10, 254-265.
• Carozza, S. E., Li, B., Wang, Q. Horel, S. and Cooper, S., Agricultural pesticides and risk of childhood cancer (2009) International Journal of Hygiene and Environmental Health, Vol. 212(2), 186-195. (Top 25 Hottest Articles!)
• Li, B., Genton, M. G. and Sherman, M., Testing the covariance structure of multivariate random fields (2008), Biometrika , Vol. 95, 813-829.
• Carozza, S. E., Li, B., Elgethun, K, and Whitworth, R., Risk of childhood cancers associated with residence in agriculturally intense areas in the United States (2008) Environmental Health Perspectives, Vol. 116, 559-565.
• Li, B., Genton, M. G. and Sherman, M., On the asymptotic joint distribution of sample space-time covariance estimators (2008) Bernoulli, Vol. 14, 228-248.
• Li, B., Erkisson, M., Raghavan, S. and Sherman, M., A geostatistical method for Texas NexRad data calibration (2008) Environmetrics, Vol. 19, 1-19.
• Li, B., Nychka, W. D. and Ammann, C. M., The “Hockey Stick” and the 1990s: A statistical perspective on reconstructing hemispheric
  temperatures (2007), Tellus, Vol. 59, 591-598.
• Li, B., Genton, M. G. and Sherman, M., A nonparametric assesment of properties of space-time covariance functions (2007) Journal of the American Statistical Association, Vol. 102, 736-744.
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Other Publications:

• Chen, M., He, X. and Li, B., Editorial. (2015) Statistica Sinica, Vol. 25, 1-3.
• Peng, R. and Li, B., Guest Editors’ introduction to the special issue on Climate Change and Human Health. (2012) Journal of Agricultural, Biological and Environmental Statistics, Vol. 17, 311-312.
• Li, B., Book review of “Solved Problems in Geostatistics” by Oy Leuangthong, K. Daniel Khan and Clayton V. Deutsch (2009) Journal of the American Statistical Association, Vol. 104, 1288.
• Li, B., Book review of “Model-based Geostatistics” by Peter J. Diggle and Paulo J. Ribeiro Jr. (2008) Journal of the American Statistical Association, Vol. 103, 1325-1326.
• Li, B., Ji, C. and Lee, J., A new concept of deep water production, storage system. (1999) Proceedings of the 18th International Conference on Offshore Mechanics and Arctic Engineering(OMAE), Houston, TX, 4024-4030.
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