My expertise is in applied mathematics, computer science and engineering. My research is in the general area of data analytics, model diagnostics and machine learning. I am the inventor and lead developer of a series of novel theoretical methods and computational related to machine learning, data analytics, model diagnostics, and data inference tools. I am also a co-inventor of LANL-patented machine-leaning methodology. Over the years, I have been the principal investigator of several projects for machine learning, model development, model analyses, uncertainty quantification and decision support
Demonstrate SmartTensors (http://tensors.lanl.gov; https://github.com/SmartTensors): a toolbox for unsupervised machine learning based on matrix/tensor factorization constrained by penalties enforcing robustness and interpretability (e.g., nonnegativity; physics and mathematical constraints; etc.). SmartTensors has been applied to analyze diverse datasets related to a wide range of problems: from COVID-19 to wildfires and climate.