Marc-Andre Renaud is a postdoctoral fellow under the supervision of Louis-Martin Rousseau. His research focuses on applying advanced optimization algorithms to the problem of radiation therapy treatment planning. In addition, he is also investigating applications of deep learning to the problem of automatic radiation therapy treatment planning. He is also co-founder of Gray, a company that aims to optimize schedules, workflows and improve patient outcomes in oncology departments using machine learning. His research is financed by an IVADO postdoctoral-entrepreneur scholarship.
A Selection of Working Papers
Renaud M-A, Fortin M-A, Lahrichi N, Rousseau L-M, (2020), Data-driven strategic planning to maintain quality of care in radiotherapy centers during the pandemic of COVID-19.
2021
Kafaei P, Cappart Q, Renaud M-A, Chapados N, Rousseau L-M, (2021), Graph neural networks and deep reinforcement learning for simultaneous beam orientation and trajectory optimization of Cyberknife, Physics in Medicine and Biology, 66(21). https://doi.org/10.1088/1361-6560/ac2bb5
Kafaei P, Cappart Q, Renaud M-A, Chapados N, Rousseau L-M, (2021), Deep Q-learning for simultaneous Beam Orientation and trajectory optimization for Cyberknife. Physics and Medecine in Biology, 66(21).