Daniell Toth is Senior Fellow with the National Institute of Statistical Sciences (NISS). Daniell is the former Senior Research Mathematical Statistician in the Office of Survey Methods Research at the U. S. Bureau of Labor Statistics and Chair of the BLS Disclosure Review Board. He is internationally recognized for his research focusing on survey methodology, especially developing tree-based methods for use on data collected from complex-sample designs. He is the author of the R-package rpms, which allows users to build and do valid inference using design consistent regression trees and forests on survey data. Daniell also works on missing data and formally private disclosure limitation methodology. He has been an associate editor of The American Statistician, Survey Methodology, and Journal of the Royal Statistics Society Series A. He is an active member and fellow of the American Statistical Association and chair elect of the 2026 Joint Statistics Meeting. Daniell was the winner of the 2025 Roger Herriot Award for Innovation in Federal Statistics.