Hooman Ramezani is an MASc student in the Department of Mechanical & Industrial Engineering at the University of Toronto and a research trainee at the Princess Margaret Cancer Centre. Hooman’s research focus is the utilization of machine learning and deep learning methodologies to develop a clinical decision support system to augment lung metastases. The aim of the project is to augment multi-disciplinary tumor board decision-making at the Princess Margaret Cancer Centre.

He is interested in the application of deep learning in vision and natural language processing (NLP) systems, and is passionate about using technology to push boundaries and positively impact communities.

  • Machine learning
  • Deep learning
  • Healthcare decision support systems
  • BASc in System Design Engineering, 2023

    University of Waterloo