A computationally efficient method for delineating irregularly shaped spatial clusters. - Juan Carlos Duque; Jared Aldstadt; Ermilson Velasquez; Jose L. Franco; Alejandro Betancourt (J. Geogr. Syst., 2011)

Developing a parallel computational implementation of AMOEBA. - Michael J. Widener; Neal Clayton Crago; Jared Aldstadt (Int. J. Geogr. Inf. Sci., 2012)

CyberGIS-Jupyter for spatially explicit agent-based modeling: a case study on influenza transmission. - Jeon-Young Kang; Jared Aldstadt; Alexander Michels; Rebecca Vandewalle; Shaowen Wang 001 (GeoSim@SIGSPATIAL, 2019)

Using multiple scale spatio-temporal patterns for validating spatially explicit agent-based models. - Jeon-Young Kang; Jared Aldstadt (Int. J. Geogr. Inf. Sci., 2019)

Using multiple scale space-time patterns in variance-based global sensitivity analysis for spatially explicit agent-based models. - Jeon-Young Kang; Jared Aldstadt (Comput. Environ. Urban Syst., 2019)

Using Multiple Scale Space-Time Patterns to Determine the Number of Replicates and Burn-In Periods in Spatially Explicit Agent-Based Modeling of Vector-Borne Disease Transmission. - Jeon-Young Kang; Jared Aldstadt (ISPRS Int. J. Geo Inf., 2021)

An integrated framework of global sensitivity analysis and calibration for spatially explicit agent-based models. - Jeon-Young Kang; Alexander Michels; Andrew T. Crooks; Jared Aldstadt; Shaowen Wang 001 (Trans. GIS, 2022)

Exploring Spatial Mismatch between Primary Care and Older Populations in an Aging Country: A Case Study of South Korea. - Jeon-Young Kang; Sandy Wong; Jinwoo Park; Jinhyung Lee; Jared Aldstadt (ISPRS Int. J. Geo Inf., 2023)