Decoding Ethiopian Abodes: Towards Classifying Buildings by Occupancy Type Using Footprint Morphology. - Daniel S. Adams; Taylor Hauser; Jessica Moehl (ICMLA, 2023)

SIGHT: Stacked Integration of Geospatial Hierarchical Typologies for Inferring Building Characteristics. - Daniel S. Adams; Jessica Moehl; Clinton Stipek; Taylor Hauser; Peter Li (IEEE Big Data, 2024)

At Risk Population Estimates for Belarus, Poland and Slovakia with Machine Learning. - Viswadeep Lebakula; Clinton Stipek; Daniel S. Adams; Justin Epting; Marie L. Urban (IEEE Big Data, 2024)

Empirically Categorizing the Built Environment in Relation to Height. - Clinton Stipek; Justin Epting; Daniel S. Adams; Viswadeep Lebakula; Taylor Hauser; Robert Stewart; Christa Brelsford; Allan Ross (IEEE Big Data, 2024)

Multivariate Testing of Sampling Techniques to Address Class Imbalance in Building Use Type Classification. - Daniel S. Adams; Taylor Hauser; Hsiuhan Lexie Yang; Peter Li (GeoAI@SIGSPATIAL, 2024)

Detecting Important Drivers of Gridded Population Modeling With Machine Learning. - Viswadeep Lebakula; Daniel S. Adams; Justin Epting; Clinton Stipek; Marie L. Urban (ICMLA, 2024)

Leveraging Open-Source Satellite-Derived Building Footprints for Height Inference. - Clinton Stipek; Taylor Hauser; Justin Epting; Jessica Moehl; Daniel S. Adams (GIScience, 2025)

A segmented approach to modeling building height: Delineating high-rise and low-rise buildings for enhanced height estimation. - Clinton Stipek; Daniel S. Adams; Philipe A. Dias; Taylor Hauser; Viswadeep Lebakula; Alexander Sorokine; Justin Epting; Jessica Moehl; Robert Stewart (Comput. Environ. Urban Syst., 2025)