Assma Alghamdi
San Francisco,CA
Overview
3
3
years of professional experience
Work History
Researcher
University of Pittsburgh
Pittsburgh, PA
08.2022 - Current
- Designed Python-based simulation tools for large-scale performance evaluation.
- Developed robust statistical Algorithms for detecting correlation change in high-dimensional data.
- Applied sequential analysis methods including CUSUM, GLR, and nonparametric correlation measures.
- Integrated Random Matrix Theory into change detection frameworks.
- Collaborated with faculty and researchers to publish findings in peer-reviewed journals.
Teaching Assistant
University of Pittsburgh
Pittsburgh, PA
08.2022 - 09.2023
- Assisted in teaching and grading for Industrial Engineering courses.
- Conducted office hours to support students in probability, statistics, and optimization topics.
- Facilitated problem-solving sessions to enhance learning outcomes.
Education
Ph.D. - Industrial Engineering
University of Pittsburgh
Pittsburgh, PA01-2025
Master of Science - Industrial Engineering
University of Pittsburgh
Pittsburgh, PA05-2021
Bachelor of Science - Industrial Engineering
University of Pittsburgh
Pittsburgh, PA05-2020
Skills
- Problem Solving
- Research
- Team Work
- Data Visualization
- Data Analysis
- Experiment Design
- Statistical Analysis
- Machine Learning
- Deep Learning
- Predictive Modeling
- Python
Timeline
Researcher
University of Pittsburgh
08.2022 - Current
Teaching Assistant
University of Pittsburgh
08.2022 - 09.2023
Ph.D. - Industrial Engineering
University of Pittsburgh
Master of Science - Industrial Engineering
University of Pittsburgh
Bachelor of Science - Industrial Engineering
University of Pittsburgh
Publications
Alghamdi, Assma, Taposh Banerjee, and Jayant Rajgopal. "Robust quickest correlation change detection in high-dimensional random vectors." Sequential Analysis (2025): 1–20.