Research Description: Liam’s research focuses on developing AI-driven, multiscale thermal models for lithium-ion batteries that incorporate materials-aware physics, as well as using machine learning techniques to predict the performance of hybridized lithium-ion anode materials and accelerate materials discovery and optimization. He holds a B.Eng in Engineering Systems and Computing from the University of Guelph, and is now a MASc candidate in the department of Materials Science & Engineering at the University of Toronto.
Contact email: liam.rocheleau@mail.utoronto.ca
Liam Rocheleau
Research Description: Liam’s research focuses on developing AI-driven, multiscale thermal models for lithium-ion batteries that incorporate materials-aware physics, as well as using machine learning techniques to predict the performance of hybridized lithium-ion anode materials and accelerate materials discovery and optimization. He holds a B.Eng in Engineering Systems and Computing from the University of Guelph, and is now a MASc candidate in the department of Materials Science & Engineering at the University of Toronto.
Contact email: liam.rocheleau@mail.utoronto.ca
