EAKOS: VAST 2009. - Lorne Leonard (IEEE VAST, 2009)

Watershed Reanalysis: Towards a National Strategy for Model-Data Integration. - Christopher J. Duffy; Lorne Leonard; Gopal Bhatt; Xuan Yu; C. Lee Giles (e-Science Workshops, 2011)

Essential Terrestrial Variable data workflows for distributed water resources modeling. - Lorne Leonard; Christopher J. Duffy (Environ. Model. Softw., 2013)

Automating data-model workflows at a level 12 HUC scale: Watershed modeling in a distributed computing environment. - Lorne Leonard; Christopher J. Duffy (Environ. Model. Softw., 2014)

Visualization workflows for level-12 HUC scales: Towards an expert system for watershed analysis in a distributed computing environment. - Lorne Leonard; Christopher J. Duffy (Environ. Model. Softw., 2016)

Cyber-Innovated Watershed Research at the Shale Hills Critical Zone Observatory. - Xuan Yu; Christopher J. Duffy; Yolanda Gil; Lorne Leonard; Gopal Bhatt; Evan Thomas (IEEE Syst. J., 2016)

Tuning Heterogeneous Computing Platforms for Large-Scale Hydrology Data Management. - Lorne Leonard; Kamesh Madduri; Christopher J. Duffy (IEEE Trans. Parallel Distributed Syst., 2016)

Graph-based visual analysis for large-scale hydrological modeling. - Lorne Leonard; Alan M. MacEachren; Kamesh Madduri (Inf. Vis., 2017)

Using machine learning models to predict and choose meshes reordered by graph algorithms to improve execution times for hydrological modeling. - Lorne Leonard (Environ. Model. Softw., 2019)

Multilevel mesh workflows towards CONUS scale watersheds: How small should triangles be to capture stream curvature for hydrological modeling? - Lorne Leonard (Environ. Model. Softw., 2019)

Development of a participatory Green Infrastructure design, visualization and evaluation system in a cloud supported jupyter notebook computing environment. - Lorne Leonard; Brian Miles; Bardia Heidari; Laurence Lin; Anthony M. Castronova; Barbara S. Minsker; Jong Lee; Charles Scaife; Lawrence E. Band (Environ. Model. Softw., 2019)

Artificial Intelligence for Modeling Complex Systems: Taming the Complexity of Expert Models to Improve Decision Making. - Yolanda Gil; Daniel Garijo; Deborah Khider; Craig A. Knoblock; Varun Ratnakar; Maximiliano Osorio; Hernán Vargas; Minh Pham 004; Jay Pujara; Basel Shbita; Binh Vu; Yao-Yi Chiang; et al. (ACM Trans. Interact. Intell. Syst., 2021)