Dr. Rebecca Nugent

Professor

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Biography

Rebecca Nugent is the Stephen E. Joyce Fienberg Professor of Statistics and Data Science at Carnegie Mellon University, where she heads the Department of Statistics and Data Science. She earned her PhD in Statistics from the University of Washington in 2006 after obtaining a B.A. in Mathematics, Statistics, and Spanish from Rice University, followed by an M.S. in Statistics from Stanford University. Nugent has received numerous teaching awards, including the American Statistical Association's Waller Award for Innovation in Statistics Education. She co-chaired a National Academy of Sciences study on Envisioning Data Science as a Discipline from an Undergraduate Perspective and is currently involved in another NAS study focused on improving the defense acquisition workforce's capability in data use. As the founding director of the Statistics & Data Science Corporate Capstone program, she facilitates experiential learning initiatives that connect student and faculty groups to data science challenges in industry, non-profits, and government. Her research primarily concentrates on clustering and classification methodologies, particularly in high-dimensional and big data contexts, as well as record linkage applications. Currently, she is focused on developing and deploying low-barrier data analysis platforms that support adaptive instruction studies in data science.

Research Interests

Requirements for Carnegie Mellon University

Doctorate Program
Requirements
GPA Requirement
Required:3.5
GRE General
Verbal
Required:158
Quantitative
Required:149
Analytical Writing
Required:4
Overall
Required:4
Prerequisites
Bachelor's degree in Psychology or related field Research experience/publications
Application Checklist
  • Online application
  • Statement of Purpose
  • Three letters of recommendation
  • Transcripts
  • GRE scores (optional but reported in profile)
  • English Proficiency (TOEFL/IELTS/Duolingo)
Specialization Notes

Admission is extremely competitive with no strict GPA cut-offs; holistic review is used.