Dr. Audrey Olivier

Assistant Professor

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Biography

Audrey Olivier holds a Diplôme d'Ingénieur from École Centrale de Nantes, France (2013), an M.S. from Columbia University (2013), and a Ph.D. in Civil Engineering Engineering Mechanics from Columbia University (2017). Her doctoral research focused on developing probabilistic data analytics tools for Structural Health Monitoring and damage detection applications. Following her Ph.D., she completed a postdoctoral appointment (2018-2020) at the Hopkins Extreme Materials Institute at Johns Hopkins University, working on developing Scientific Machine Learning algorithms for materials modeling applications. She served as an Associate Research Scientist at Columbia University (2020-2021), where she worked on data analytics tools to optimize emergency medical services deployment in the greater New York City area. Dr. Olivier's research interests lie at the intersection of physics-based modeling, data analytics, and uncertainty quantification, focusing on building resilient smart urban environments through Structural Health Monitoring and using sensing data to monitor structures' behavior and detect potential damage onset. Her work addresses the rapidly evolving trends of urbanization and climate-related hazards that impose considerable loads on aging infrastructure, motivating the development of reliable health monitoring and damage detection techniques for infrastructure management. In the smart-city context, she leverages probabilistic data analytics tools to optimize processes in infrastructure systems, enhancing computational mechanics by combining physics-based simulations with data-driven methods.

Research Interests

Experience

Associate Research Scientist

2020-01-01 — 2021-01-01

Columbia University • New York City, NY

Worked on data analytics tools optimization for emergency medical services deployment in the greater New York City area.

Postdoctoral Researcher

2018-01-01 — 2020-01-01

Hopkins Extreme Materials Institute, Johns Hopkins University • Baltimore, MD

Developed Scientific Machine Learning algorithms for materials modeling applications.

Requirements for University of Southern California

Master Program
Requirements
GPA Requirement
Required:3
TOEFL
Listening
Required:20
Reading
Required:20
Writing
Required:20
Speaking
Required:20
Total
Required:100
GRE General
Prerequisites
Bachelor's degree in engineering or related science
Application Checklist
  • Official transcripts
  • GRE General scores
  • TOEFL scores (International)
  • Three letters of recommendation
  • Personal Statement
Specialization Notes

Requires general GRE for all graduate degrees.