Bio

S. Mohammad Hosseinian is an assistant professor in the Edward P. Fitts Department of Industrial and Systems Engineering. He earned his Ph.D. in Industrial Engineering from Texas A&M University in 2021. Following his doctoral studies, he worked as a postdoctoral researcher in the Department of Computational Applied Mathematics and Operations Research at Rice University, with a concurrent appointment in the Department of Radiation Oncology at MD Anderson Cancer Center. Before joining NC State, he was an Assistant Professor of Industrial and Systems Engineering at the University of Cincinnati, where he was also an Associate Research Member of the University of Cincinnati Cancer Center.

Area(s) of Expertise

Hosseinian’s primary research interests include the theory and computational aspects of optimization methodologies and their applications in healthcare/medical decision-making.

Publications

• Cost-effectiveness of personalized policies for implementing organ-at-risk sparing adaptive radiation therapy in head and neck cancer , Physics and Imaging in Radiation Oncology (2025)
• Externally validated digital decision support tool for time-to-osteoradionecrosis risk-stratification using right-censored multi-institutional observational cohorts , Radiotherapy and Oncology (2025)
• Geometric optimization of dose distribution in spatially fractionated radiation therapy , Physics in Medicine and Biology (2025)
• Optimal timing of organs-at-risk-sparing adaptive radiation therapy for head-and-neck cancer under re-planning resource constraints , Physics and Imaging in Radiation Oncology (2025)
• Cluster-Based Toxicity Estimation of Osteoradionecrosis Via Unsupervised Machine Learning: Moving Beyond Single Dose-Parameter Normal Tissue Complication Probability by Using Whole Dose-Volume Histograms for Cohort Risk Stratification , International Journal of Radiation Oncology*Biology*Physics (2024)
• Markov models for clinical decision‐making in radiation oncology: A systematic review , Journal of Medical Imaging and Radiation Oncology (2024)
• Strategy investments in zero-sum games , Optimization Letters (2024)
• Variable-Interval Temporal Feathering to Optimize Organ-at-Risk Repair for Head and Neck Adaptive Radiotherapy , medRxiv (2024)
• Cluster-Based Toxicity Estimation of Osteoradionecrosis via Unsupervised Machine Learning: Moving Beyond Single Dose-Parameter Normal Tissue Complication Probability by Using Whole Dose-Volume Histograms for Cohort Risk Stratification , medRxiv (2023)
• Code and Data Repository for Combination Chemotherapy Optimization with Discrete Dosing , INFORMS journal on computing (2023)

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