معرفی
Talayeh Razzaghi is an Assistant Professor at the University of Oklahoma's School of Industrial and Systems Engineering. Her research focuses on developing data-driven machine learning and AI models for healthcare, cyber-physical systems, and smart manufacturing. She addresses challenges in imperfect datasets, including high-dimensionality, class imbalance, and missing values. Her work emphasizes healthcare disparities, particularly cancer outcomes in women and under-resourced communities.
Education:
- Ph.D., Industrial Engineering, University of Central Florida
- M.S., Industrial and Systems Engineering, Sharif University of Technology, Iran
- B.S., Applied Mathematics, University of Tehran, Iran
Research Interests: Machine learning with imperfect data, health disparities, disease risk stratification, AI-based community health monitoring, predictive analytics in cyber-physical systems. Her lab explores applications in personalized medical diagnosis, patient-centered outcomes prediction, and smart biomanufacturing.
Key Articles Trends: Recent work bridges machine learning with healthcare challenges (e.g., cesarean delivery prediction in obese patients, cardiovascular risk in cancer survivors) and industrial systems (e.g., protein titer optimization, federated learning frameworks).
Awards:
- NSF CAREER Award (2024)
- OU VPRP Excellence in Research Award (2022, 2023)
- INFORMS Senior Membership (2024–present)
Advising & Grants: Active in mentoring graduate students (applications encouraged via email). Secured NSF funding through her CAREER Award and institutional grants. Serves as Associate Editor for Energy Systems and holds leadership roles in IISE and INFORMS.
Labs & Teams: Leads a research group advancing AI in precision health and industrial optimization. Collaborates with interdisciplinary teams on federal grants and industry partnerships.
