publications

2026

  1. A Bayesian Framework for Built-in Input Dimension Reduction for Gaussian Process Modeling
    Eric Herrison Gyamfi, Emily L. Kang, Bledar A. Konomi, and Guang Lin
    2026
    Submitted
  2. DeepONet Retrieval of CO2-Concentration Profiles from Orbiting Carbon Observatory-2 Radiance Measurements with Conformal Uncertainty Quantification
    Richard Lucas, Emily L. Kang, Jonathan M. Hobbs, and Amy J. Braverman
    2026
    Submitted
  3. Efficient Gaussian Process Modeling for Large Replicated and Censored Data in Industrial Research
    Ying Zhang, Emily L. Kang, and Shuo Li
    2026
    Submitted
  4. Bayesian Climate Model Integration: Moving Beyond Weights Toward Uncertainty Quantification
    Ayesha Ekanayaka, Emily L. Kang, Peter Kalmus, and Seungwon Lee
    2026
    Submitted

2025

  1. A multivariate spatial statistical model for statistical downscaling of sea surface temperature in the Great Barrier Reef region
    Ayesha Ekanayaka, Emily L. Kang, Amy Braverman, and Peter Kalmus
    Journal of the Royal Statistical Society Series C: Applied Statistics, Nov 2025
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  2. A Practical Tool for Visualizing and Measuring Model Selection Uncertainty
    Sheng Ren, Peng Wang, and Emily L. Kang
    Stat, Mar 2025
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  3. PPD-CPP: Pointwise predictive density calibrated-power prior in dynamically borrowing historical information
    Shixuan Wang, Jing Zhang, Emily L. Kang, and Bin Zhang
    arXiv preprint arXiv:2509.25688, Sep 2025
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  4. Enhancing Gaussian Processes for Surrogate Modeling: A Review of Dimension Reduction Techniques for Input Variables
    Eric Herrison Gyamfi, Bledar A. Konomi, Guang Lin, and Emily L. Kang
    In Handbook of Statistical Methods for Computer Models: Uncertainty Quantification, Sep 2025
    In press
    PDF

2024

  1. Ecopro: Ecological Projection Digital Twin
    Seungwon Lee, Peter Kalmus, Antonio Ferraz, Alex Goodman, Kyle Pearson, Gary Doran, Flynn Platt, and 7 more authors
    In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Jul 2024
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  2. Recursive nearest neighbor co-kriging models for big multi-fidelity spatial data sets
    Si Cheng, Bledar A. Konomi, Georgios Karagiannis, and Emily L. Kang
    Environmetrics, Feb 2024
    HTML DOI

2023

  1. Bayesian Latent Variable Co-kriging Model in Remote Sensing for Quality Flagged Observations
    Bledar A. Konomi, Emily L. Kang, Ayat Almomani, and Jonathan Hobbs
    Journal of Agricultural, Biological and Environmental Statistics, Feb 2023
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2022

  1. Traffic restrictions during the 2008 Olympic Games reduced urban heat intensity and extent in Beijing
    Bo Yang, Hongxing Liu, Emily L. Kang, Song Shu, Min Xu, Bin Wu, Richard A. Beck, and 2 more authors
    Communications Earth & Environment, Feb 2022
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  2. Past the precipice? Projected coral habitability under global heating
    Peter Kalmus, Ayesha Ekanayaka, Emily L. Kang, Mark Baird, and Michelle Gierach
    Earth’s Future, Feb 2022
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  3. Statistical Downscaling of Sea Surface Temperature Projections with a Multivariate Gaussian Process Model
    Ayesha Ekanayaka, Peter Kalmus, Emily L. Kang, and Amy Braverman
    In Workshop on Gaussian Processes, Spatiotemporal Modeling, and Decision-Making Systems (GPSMDMS) at the International Conference on Neural Information Processing Systems (NeurIPS), Feb 2022
    PDF HTML

2021

  1. Hierarchical Bayesian nearest neighbor co-kriging Gaussian process models; an application to intersatellite calibration
    Si Cheng, Bledar A. Konomi, Jessica L. Matthews, Georgios Karagiannis, and Emily L. Kang
    Spatial Statistics, Feb 2021
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  2. Computer Model Emulation with High-Dimensional Functional Output in Large-Scale Observing System Uncertainty Experiments
    Pulong Ma, Anirban Mondal, Bledar A. Konomi, Jonathan Hobbs, Joon Jin Song, and Emily L. Kang
    Technometrics, Feb 2021
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  3. Spatio-temporal Cokriging method for assimilating and downscaling multi-scale remote sensing data
    Bo Yang, Hongxing Liu, Emily L. Kang, Song Shu, Min Xu, Bin Wu, Richard A. Beck, and 2 more authors
    Remote Sensing of Environment, Feb 2021
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  4. Modeling Large Multivariate Spatial Data with a Multivariate Fused Gaussian Process
    Emily L. Kang, Miaoqi Li, Kerry Cawse-Nicholson, and Amy Braverman
    Journal of the Indian Statistical Association, Feb 2021
    PDF
  5. Improving Satellite Waveform Altimetry Measurements With a Probabilistic Relaxation Algorithm
    Song Shu, Hongxing Liu, Frédéric Frappart, Emily L. Kang, Bo Yang, Min Xu, Yan Huang, and 5 more authors
    IEEE Transactions on Geoscience and Remote Sensing, Jun 2021
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2020

  1. A Fused Gaussian Process Model for Very Large Spatial Data
    Pulong Ma and Emily L. Kang
    Journal of Computational and Graphical Statistics, Jun 2020
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  2. Sensitivity and uncertainty quantification for the ECOSTRESS evapotranspiration algorithm – DisALEXI
    Kerry Cawse-Nicholson, Amy Braverman, Emily L. Kang, Miaoqi Li, Margaret Johnson, Gregory Halverson, Martha Anderson, and 3 more authors
    International Journal of Applied Earth Observation and Geoinformation, Jun 2020
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  3. Spatial analysis and visualization of global data on multi-resolution hexagonal grids
    Tim Stough, Noel Cressie, Emily L. Kang, Anna M. Michalak, and Kevin Sahr
    Japanese Journal of Statistics and Data Science, Jun 2020
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  4. Assessing the effects of bus stop relocation on street robbery
    Lin Liu, Minxuan Lan, John E. Eck, and Emily L. Kang
    Computers, Environment and Urban Systems, Jun 2020
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  5. MCEN: a method of simultaneous variable selection and clustering for high-dimensional multinomial regression
    Sheng Ren, Emily L. Kang, and Jason L. Lu
    Statistics and Computing, Jun 2020
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  6. Spatiotemporal data fusion for massive sea surface temperature data from MODIS and AMSR-E instruments
    Pulong Ma and Emily L. Kang
    Environmetrics, Jun 2020
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2019

  1. Randomized algorithms of maximum likelihood estimation with spatial autoregressive models for large-scale networks
    Miaoqi Li and Emily L. Kang
    Statistics and Computing, Jun 2019
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  2. Spatial Statistical Downscaling for Constructing High-Resolution Nature Runs in Global Observing System Simulation Experiments
    Pulong Ma, Emily L. Kang, Amy J. Braverman, and Hai M. Nguyen
    Technometrics, Jun 2019
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  3. A spectral space partition guided ensemble method for retrieving chlorophyll-a concentration in inland waters from Sentinel-2A satellite imagery
    Min Xu, Hongxing Liu, Richard Beck, John Lekki, Bo Yang, Song Shu, Emily L. Kang, and 5 more authors
    Journal of Great Lakes Research, Jun 2019
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  4. Hierarchical Bayesian Model Based on Robust Fixed Rank Filter for Fusing MODIS SST and AMSR-E SST
    Yuxin Zhu, Emily L. Kang, Yanchen Bo, Jinzong Zhang, Yuexiang Wang, and Qingxin Tang
    Photogrammetric Engineering & Remote Sensing, Jun 2019
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  5. Computationally efficient nonstationary nearest-neighbor Gaussian process models using data-driven techniques
    Bledar A. Konomi, Ahmad A. Hanandeh, Pulong Ma, and Emily L. Kang
    Environmetrics, Jun 2019
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  6. An additive approximate Gaussian process model for large spatio-temporal data
    Pulong Ma, Bledar A. Konomi, and Emily L. Kang
    Environmetrics, Jun 2019
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2018

  1. Ecosystem responses to elevated CO_2 using airborne remote sensing at Mammoth Mountain, California
    Kerry Cawse-Nicholson, Joshua B. Fisher, Charles A. Famiglietti, Amy Braverman, Florian M. Schwandner, Jennifer L. Lewicki, Philip A. Townsend, and 9 more authors
    Biogeosciences, Jun 2018
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  2. Improving MODIS snow products with a HMRF-based spatio-temporal modeling technique in the Upper Rio Grande Basin
    Yan Huang, Hongxing Liu, Bailang Yu, Jianping Wu, Emily L. Kang, Min Xu, Shujie Wang, and 2 more authors
    Remote Sensing of Environment, Jun 2018
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2017

  1. Spatial data fusion for large non-Gaussian remote sensing datasets
    Hongxiang Shi and Emily L. Kang
    Stat, Jun 2017
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  2. Uncertainty Quantification Using the Nearest Neighbor Gaussian Process
    Hongxiang Shi, Emily L. Kang, Bledar A. Konomi, Kumar Vemaganti, and Sandeep Madireddy
    In New Advances in Statistics and Data Science, Jun 2017
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2016

  1. Hot Enough for You? A Spatial Exploratory and Inferential Analysis of North American Climate-Change Projections
    Noel Cressie and Emily L. Kang
    Mathematical Geosciences, Jun 2016
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2015

  1. Computational and statistical analysis of metabolomics data
    S. Ren, A. A. Hinzman, Emily L. Kang, R. D. Szczesniak, and L. J. Lu
    Metabolomics, Jun 2015
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  2. A Robust Fixed Rank Kriging Method for Improving the Spatial Completeness and Accuracy of Satellite SST Products
    Yuxin Zhu, Emily L. Kang, Yanchen Bo, Qingxin Tang, Jin Cheng, and Yuxiang He
    IEEE Transactions on Geoscience and Remote Sensing, Sep 2015
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2013

  1. Bayesian Hierarchical ANOVA of Regional Climate-Change Projections from NARCCAP Phase II
    Emily L. Kang and Noel Cressie
    International Journal of Applied Earth Observation and Geoinformation, Sep 2013
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  2. Modeling Spatial Frailties in Survival Analysis of Cucurbit Downy Mildew Epidemics
    P. S. Ojiambo and Emily L. Kang
    Phytopathology, Sep 2013
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  3. Regression models with memory for the linear response of turbulent dynamical systems
    Emily L. Kang, John Harlim, and Andrew J. Majda
    Communications in Mathematical Sciences, Sep 2013
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2012

  1. Filtering nonlinear spatio-temporal chaos with autoregressive linear stochastic models
    Emily L. Kang and John Harlim
    Physica D: Nonlinear Phenomena, Sep 2012
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  2. Combining Outputs from the North American Regional Climate Change Assessment Program by Using A Bayesian Hierarchical Model
    Emily L. Kang, Noel Cressie, and Stephan R. Sain
    Journal of the Royal Statistical Society Series C: Applied Statistics, Mar 2012
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  3. Filtering Partially Observed Multiscale Systems with Heterogeneous Multiscale Methods–Based Reduced Climate Models
    Emily L. Kang and John Harlim
    Monthly Weather Review, Mar 2012
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2011

  1. Bayesian Inference for the Spatial Random Effects Model
    Emily L. Kang and Noel Cressie
    Journal of the American Statistical Association, Mar 2011
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2010

  1. Using temporal variability to improve spatial mapping with application to satellite data
    Emily L. Kang, Noel Cressie, and Tao Shi
    Canadian Journal of Statistics, Mar 2010
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  2. High-Resolution Digital Soil Mapping: Kriging for Very Large Datasets
    Noel Cressie and Emily L. Kang
    In Proximal Soil Sensing, Mar 2010
    HTML DOI
  3. Fixed Rank Filtering for Spatio-Temporal Data
    Noel Cressie, Tao Shi, and Emily L. Kang
    Journal of Computational and Graphical Statistics, Mar 2010
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2009

  1. Statistical analysis of small-area data based on independence, spatial, non-hierarchical, and hierarchical models
    Emily L. Kang, Desheng Liu, and Noel Cressie
    Computational Statistics & Data Analysis, Mar 2009
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  2. Smoothing splines for trend estimation and prediction in time series
    R. Morton, Emily L. Kang, and B. L. Henderson
    Environmetrics, Mar 2009
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