Yasin Fatemi, PhD Candidate
yzf0024@auburn.edu
SHELBY Center, Room 3331
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Short Bio
Yasin is a PhD candidate in Industrial and Systems Engineering and a master's student in Data Science at Auburn University. His research focuses on machine learning, deep learning, simulation, network analysis and spatial analysis in healthcare, with a particular emphasis on women's birth outcomes, including factors contributing to low birth weight and preterm birth. He has extensive experience working with statistical modeling, GIS-based healthcare analysis and predictive analytics using large-scale healthcare datasets. In addition to his research, Yasin serves as both an instructor and teaching assistant in the Mathematics, Political Science, and Industrial & Systems Engineering departments. His academic and professional work combines data science, healthcare analytics and systems engineering to address complex real-world problems through innovative analytical approaches.
Education
MS, Industrial Engineering Tarbiat Modares University 2015-2017
Data Science Auburn Uiversity Current
Industrial Eng (PhD Candidate) Auburn Uiversity Current
Professional Experience
- PhD Candidate in Industrial and Systems Engineering and MS student in Data Science at Auburn University.
- Instructor and Teaching Assistant in the Mathematics, Political Science and Industrial & Systems Engineering departments.
- Experienced in applying machine learning, statistical analysis, and optimization methods to real-world health care and engineering problems.
- Worked on predictive modeling, simulation and data analytics projects using large-scale datasets.
- Skilled in Python, R, SQL, GIS, deep learning and health care data analysis.
- Conducted interdisciplinary projects involving healthcare systems, public health analytics and decision-support modeling.
Innovation
- Research interests include machine learning, deep learning, simulation, network analysis and spatial analysis.
- Focused on healthcare analytics, particularly women's birth outcomes and maternal health disparities.
- Investigating factors contributing to low birth weight and preterm birth using predictive and spatial models.
- Applying GIS and network-based methods to study healthcare accessibility and population health outcomes.
- Developing data-driven approaches for healthcare decision-making and policy analysis.
- Interested in integrating artificial intelligence and systems engineering methods into public health research.
Engagement
President of the Data Science Society at Auburn University, leading student engagement initiatives, academic events and professional development activities in data science and analytics.
