Nicholas Rios

Nicholas Rios is an Assistant Professor of Statistics at George Mason University (GMU), where he has been affiliated since August 2022. He holds a PhD in Statistics from The Pennsylvania State University (2022), an MS from Montclair State University, and a BS from the University of Delaware. His research focuses on experimental design under real-world constraints, computational statistics, functional data analysis, Gaussian processes, and compositional data analysis, with applications in chemical engineering and pharmaceuticals.

Dr. Rios teaches applied statistics (STAT 554) and emphasizes critical thinking in statistical methodology. His doctoral work developed novel algorithms for efficient mixture experiments, particularly addressing the impact of component addition order. His current research bridges theoretical statistical methods with practical industrial challenges, leveraging his expertise in high-dimensional data and constrained experimental designs.

His recent publications (2022–2025) explore advanced experimental design techniques, bootstrap aggregation for generalized linear models, and compositional data analysis in chemical recycling. While no scientific awards are explicitly mentioned, his work demonstrates significant contributions to optimizing experimental setups in constrained environments.

Dr. Rios’ advising and grants are not detailed in the provided texts, though his CV (linked) may provide further insights into collaborative projects or funding. He actively contributes to statistical education and maintains a personal website for professional engagement.