Lyndsay Shand

Observation Pathway Lead

Biography

Lyndsay has expertise in spatial and spatio-temporal statistics, point process models, Bayesian hierarchical models, and statistical methods for remotely-sensed data, atmospheric, and climate applications. For the past eight years, she has developed space-time statistical methods for observational environmental and climate data. As principal investigator of Sandia’s first Marine Cloud Brightening LDRD, her interdisciplinary team developed data-driven methods to understand the local impacts of ship emissions. Lyndsay is also a key contributor to Sandia’s Climate Security Strategy and holds an adjunct faculty position in the Department of Statistics at University of Illinois Urbana-Champaign.

Publications

Lyndsay Shand, Kelsie Larson, Erika Roesler, don lyons, Skyler Gray, (2022). An Optical Flow Approach to Tracking Ship Track Behavior Using GOES-R Satellite Imagery IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing https://doi.org/10.1109/JSTARS.2022.3193024 Publication ID: 80910

Lyndsay Shand, (2021). Integrative data-driven approaches for characterization & prediction of aerosol-cloud processes https://doi.org/10.2172/1899681 Publication ID: 76630

James Tucker, Lyndsay Shand, Kenny Chowdhary, (2021). Multimodal Bayesian registration of noisy functions using Hamiltonian Monte Carlo Computational Statistics and Data Analysis https://doi.org/10.1016/j.csda.2021.107298 Publication ID: 78778

Jennifer Frederick, Diana Bull, Robert Abbott, Lyndsay Shand, (2021). Guest Lecture at the Naval Postgraduate School: The National Laboratory System & Sandia National Laboratories https://www.osti.gov/servlets/purl/1894757 Publication ID: 76459

Lyndsay Shand, Kelsie Larson, Andrea Staid, Erika Roesler, Donald Lyons, Katherine Simonson, Lekha Patel, James Hickey, Skyler Gray, (2021). Local limits of detection for anthropogenic aerosol-cloud interactions https://doi.org/10.2172/1855009 Publication ID: 75923

Lyndsay Shand, (2021). Opportunities and challenges for openly publishing statistics research for national defense applications https://doi.org/10.2172/1862181 Publication ID: 77930

Edmundo Corona, Sharlotte Kramer, Brian Lester, Amanda Jones, B. Sanborn, Lyndsay Shand, Carter Fietek, (2021). Thermal-Mechanical Elastic-Plastic and Ductile Failure Model Calibrations for 304L Stainless Steel Alloy https://doi.org/10.2172/1769256 Publication ID: 77228

Andrea Staid, Kelsie Larson, Lyndsay Shand, Erika Roesler, Donald Lyons, (2020). Observations of ship-induced cloud tracks and methods for quantifying the duration of track visibility https://doi.org/10.2172/1832732 Publication ID: 71912

Lekha Patel, Lyndsay Shand, James Tucker, Jose Huerta, (2020). Assessing Extreme Value Analysis to predict rare events from the Global Terrorism Database https://www.osti.gov/servlets/purl/1825584 Publication ID: 71177

Lekha Patel, Lyndsay Shand, (2020). Simulating cloud-aerosol interactions made by ship emissions https://www.osti.gov/servlets/purl/1824931 Publication ID: 71141

Lyndsay Shand, Lekha Patel, (2020). Simulating cloud-aerosol interactions made by ship emissions https://www.osti.gov/servlets/purl/1811613 Publication ID: 74253

Lekha Patel, Jose Huerta, Lyndsay Shand, William Miller, James Tucker, (2020). Assessing Extreme Value Analysis to predict rare events from the Global Terrorism Database https://www.osti.gov/servlets/purl/1811818 Publication ID: 74294

Kamaljit Chowdhary, James Tucker, Lyndsay Shand, (2020). Bayesian Function Registration in R1 https://www.osti.gov/servlets/purl/1812166 Publication ID: 74345

Lyndsay Shand, (2020). Local limits of detection for anthropogenic aerosol-cloud interactions https://www.osti.gov/servlets/purl/1762578 Publication ID: 70818

Lyndsay Shand, (2019). Data-driven inferences for aerosol and marine low-cloud interactions using ship-based databases and open-source satellite imagery https://www.osti.gov/servlets/purl/1643525 Publication ID: 66619

Lyndsay Shand, (2019). Sandia Overview https://www.osti.gov/biblio/1646427 Publication ID: 66497

Lyndsay Shand, Robert Knepper, Dan Bolintineanu, Lauren Wilson, D. Kittell, (2019). Nonstationary Spatial Methods for Microstructure Reconstruction https://www.osti.gov/servlets/purl/1641429 Publication ID: 70175

Lyndsay Shand, (2019). Data-driven Approach to Cloud-Aerosol Interactions https://www.osti.gov/biblio/1645367 Publication ID: 68889

James Tucker, Trevor Harris, Bo Li, Lyndsay Shand, (2019). Identifying Outliers in Functional Data with Elastic Depth https://www.osti.gov/servlets/purl/1644855 Publication ID: 67957

Lyndsay Shand, Andrea Staid, Erika Roesler, (2019). Local limits of detection for anthropogenic aerosol-cloud interactions https://www.osti.gov/servlets/purl/1593214 Publication ID: 64350

James Tucker, Lyndsay Shand, (2018). Identifying Phase and Amplitude Extremes in Functional Data with Elastic Depth https://www.osti.gov/servlets/purl/1561429 Publication ID: 64099

Lyndsay Shand, (2018). Spatially varying auto-regressive models for prediction of new HIV diagnoses https://www.osti.gov/servlets/purl/1569194 Publication ID: 63009

James Tucker, John Lewis, Lyndsay Shand, Jonathan Lane, (2018). Bayesian Modeling of Self-Exciting Marked Point Processes with Missing Histories https://www.osti.gov/servlets/purl/1527084 Publication ID: 62604

John Lewis, James Tucker, Lyndsay Shand, (2018). Bayesian Modeling of Self-Exciting Marked Point Processes with Missing Histories https://www.osti.gov/servlets/purl/1499221 Publication ID: 60971

Shuyue Guo, Marcia Cooper, Lyndsay Shand, (2017). A Statistical Representation of Pyrotechnic Research Igniter Output https://doi.org/10.1063/1.5044973 Publication ID: 58367

Shuyue Guo, Marcia Cooper, Lyndsay Shand, (2017). A Statistical Representation of Pyrotechnic Igniter Output https://doi.org/10.1063/1.5044973 Publication ID: 57444

Shuyue Guo, Marcia Cooper, Lyndsay Shand, (2017). A Statistical Representation of Pyrotechnic Igniter Output https://doi.org/10.1063/1.5044973 Publication ID: 57720

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