Nathaniel (Nate) Charest, Ph.D., is a cheminformatician and modeler at UL Research Institutes’ Chemical Insights, focusing on cheminformatics research and applying machine and statistical learning to computational chemistry. His work involves integrating non-targeted analysis exposure data with bioactivity datasets to enhance toxicity testing and chemical prioritization.

Previously, Nate was a research scientist, developing platforms for chemical data analysis and creating predictive models for chemical properties. He also completed postdoctoral research using machine learning to model sequence-activity relationships from RNA-seq datasets, successfully predicting validated active ribozymes.

Nate holds a Ph.D. in Chemistry from the University of California Santa Barbara and a B.S. in Biochemistry from the same institution.  

ORCiD: 0000-0003-4252-0365