From HPC Performance to Climate Modeling: Transforming Methods for HPC Predictions into Models of Extreme Climate Conditions. - Ryan McKinney; Vivek K. Pallipuram; Rodrigo Vargas; Michela Taufer (e-Science, 2015)

Data analytics for modeling soil moisture patterns across united states ecoclimatic domains. - Thomas Kitson; Paula Olaya; Elizabeth Racca; Michael R. Wyatt II; Mario Guevara; Rodrigo Vargas; Michela Taufer (IEEE BigData, 2017)

A low-cost modular data-acquisition system for monitoring biometeorological variables. - Angel Castro 001; Juan F. Martínez-Osuna; Raúl Michel; Martín Escoto-Rodríguez; Stephen H. Bullock; Alejandro Cueva; Eulogio López-Reyes; Janet Reimer; Mario Salazar; Samuel Villarreal; Rodrigo Vargas (Comput. Electron. Agric., 2017)

SOMOSPIE: A Modular SOil MOisture SPatial Inference Engine Based on Data-Driven Decisions. - Danny Rorabaugh; Mario Guevara; Ricardo M. Llamas; Joy Kitson; Rodrigo Vargas; Michela Taufer (eScience, 2019)

SOMOSPIE: A modular SOil MOisture SPatial Inference Engine based on data driven decision. - Danny Rorabaugh; Mario Guevara; Ricardo M. Llamas; Joy Kitson; Rodrigo Vargas; Michela Taufer (CoRR, 2019)

Spatial Gap-Filling of ESA CCI Satellite-Derived Soil Moisture Based on Geostatistical Techniques and Multiple Regression. - Ricardo M. Llamas; Mario Guevara; Danny Rorabaugh; Michela Taufer; Rodrigo Vargas (Remote. Sens., 2020)

Augmenting Singularity to Generate Fine-grained Workflows, Record Trails, and Data Provenance. - Dominic Kennedy; Paula Olaya; Jay F. Lofstead; Rodrigo Vargas; Michela Taufer (e-Science, 2022)

Downscaling Satellite Soil Moisture Using a Modular Spatial Inference Framework. - Ricardo M. Llamas; Leobardo Valera; Paula Olaya; Michela Taufer; Rodrigo Vargas (Remote. Sens., 2022)

Enabling Scalability in the Cloud for Scientific Workflows: An Earth Science Use Case. - Paula Olaya; Jakob Lüttgau; Camila Roa; Ricardo M. Llamas; Rodrigo Vargas; Sophia Wen; I-Hsin Chung; Seetharami R. Seelam; Yoonho Park; Jay F. Lofstead; Michela Taufer (CLOUD, 2023)

GEOtiled: A Scalable Workflow for Generating Large Datasets of High-Resolution Terrain Parameters. - Camila Roa; Paula Olaya; Ricardo M. Llamas; Rodrigo Vargas; Michela Taufer (HPDC, 2023)

End-to-end Integration of Scientific Workflows on Distributed Cyberinfrastructures: Challenges and Lessons Learned with an Earth Science Application. - Camila Roa; Mats Rynge; Paula Olaya; Karan Vahi; Todd Miller; James Griffioen; Shelley Knuth; John Goodhue; Dávid Hudák; Alana Romanella; Ricardo M. Llamas; Rodrigo Vargas; et al. (UCC, 2023)

Building Trust in Earth Science Findings through Data Traceability and Results Explainability. - Paula Olaya; Dominic Kennedy; Ricardo M. Llamas; Leobardo Valera; Rodrigo Vargas; Jay F. Lofstead; Michela Taufer (IEEE Trans. Parallel Distributed Syst., 2023)

Multi-Modal Transformer for Compressive LiDARs Using Hyperspectral Imaging Side-Information. - Nestor Porras-Diaz; Andres Ramirez-Jaime; Gonzalo R. Arce; Rodrigo Vargas; David J. Harding; Mark Stephen; James MacKinnon (IGARSS, 2024)

Transformer End-to-End Optimization of Compressive LiDARs Using Imaging Spectroscopy Side Information. - Nestor Porras-Diaz; Andres Ramirez-Jaime; Gonzalo R. Arce; Karelia Pena-Pena; David J. Harding; Mark Stephen; James MacKinnon; Rodrigo Vargas (IEEE Trans. Geosci. Remote. Sens., 2024)

An autocorrelated conditioned Latin hypercube method for temporal or spatial sampling and predictions. - Van Huong Le; Rodrigo Vargas (Comput. Geosci., 2024)