Dr. Elizabeth Salerno

Assistant Professor

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Biography

Elizabeth Salerno is an Assistant Professor in Applied Exercise Science at the University of Michigan. She previously served as an Assistant Professor in the Division of Public Health Sciences in the Department of Surgery at Washington University School of Medicine in St. Louis. Dr. Salerno completed her PhD in Kinesiology with an emphasis on exercise psychology at the University of Illinois at Urbana-Champaign in 2017. She also undertook a postdoctoral fellowship as a Cancer Prevention Fellow at the National Cancer Institute. Additionally, Dr. Salerno earned her MPH from Johns Hopkins Bloomberg School of Public Health, focusing on biostatistical and epidemiological methods for public health and clinical research. Her research interests lie in understanding the determinants and outcomes of physical activity behavior, especially at the intersection of aging and cancer, to maximize functional health, quality of life, and survival among cancer survivors through evidence-based interventions.

Research Interests

Experience

Assistant Professor

2025-09-11 — Present

University of Michigan • Ann Arbor, MI

Assistant Professor in Applied Exercise Science, focusing on research and instruction.

Assistant Professor

— Present

Washington University School of Medicine • St. Louis, MO

Assistant Professor in the Division of Public Health Sciences, specializing in surgery.

Requirements for University of Michigan

Master Program
Requirements
GPA Requirement
Required:3.5
TOEFL
Total
Required:84
GRE General
Verbal
Required:155
Verbal Percentile
Required:50
Quantitative
Required:168
Quantitative Percentile
Required:50
Analytical Writing
Required:3.6
Writing Percentile
Required:50
Prerequisites
Bachelor degree in engineering, physics, or mathematics Calculus Physics
Application Checklist
  • Rackham Graduate School Application
  • Official Transcripts
  • 3 Letters of Recommendation
  • Academic Statement of Purpose
  • Personal Statement
  • CV/Resume
Specialization Notes

Department of Electrical Engineering and Computer Science