Hamed Shourabizadeh is a PhD candidate in the Department of Mechanical & Industrial Engineering at the University of Toronto. He received his MSc in Industrial Engineering from Sharif University of Technology (2015) and BSc in Industrial Engineering from Iran University of Science and Technology (2013). Prior to his PhD, Hamed worked as a researcher for the The Scientific and Technological Research Council of Turkey (TÜBİTAK) where he optimized hospital inventory systems. Hamed’s research is focused on the application of ML/AI and operations research to healthcare systems. His PhD project is on the application of ML to predict the survival of bone marrow transplant patients. The research is in collaboration with Princess Margaret Cancer Centre in Toronto.
A Selection of Working Papers
Zheng K, Shourabizadeh H, Aleman D M, Rousseau L-M, Bhat M, (2024), Machine Learning for predicting graft survival following liver transplantation.
Shourabizadeh H, Aleman D M, Rousseau L-M, Zheng K, Bhat M, (2024), Classification-augmented survival estimation (CASE): A novel method for individualized long-term survival prediction with applcation to liver transplantation.
Journal and Conference Publications - 2024
Qu Y, Shourabizadeh H, Subramanian A, Aleman D.M., Rousseau L-M, Law A.D., Viswabandya A., Michelis F.V., (2024), Differential impact of CD34+ cell dose for different age groups in allogeneic hematopoietic cell transplantation for acute leukemia: a machine learning-based discovery, Experimental Hematology.
2023
Shourabizadeh H, M. Aleman D, Rousseau L-M, D. Law A, Viswabandya A, Michelis F.V., (2023), Machine learning for the prediction of survival post-allogeneic hematopoietic cell transplantation: A single-center experience, Acta Haematologica, 147(3): 280-291.