Application of Machine Learning Algorithms to Mineral Prospectivity Mapping | Department of Earth, Ocean and Atmospheric Sciences

Faculty of Science Department of Earth, Ocean and Atmospheric Sciences

Application of Machine Learning Algorithms to Mineral Prospectivity Mapping

Nov 30 2016 12:30PM

Room 203, Graduate Student Centre (6371 Crescent Road)

Thesis Defense

Defense Level: PhD Thesis Defense

Speaker: Justin Granek

Dr. Eldad Haber

Jun 12 9:00AM - 12:00PM

Graduate Student Centre - Room 200

Thesis Defense

Turbulent heat fluxes and katabatic flow at glacier surfaces: insights from measurements and modelling

PhD Thesis Defense

Speaker: Cole Lord-May

Supervised by: Valentina Radic

May 27 9:00AM - 12:00PM

ESB 5108

Thesis Defense

Spalling and strainbursting in deep mining tunnels - data driven and numerical analyses to improve ground support design and tunnel reliability

PhD Thesis Defense

Speaker: Justin Roy

Supervised by: Erik Eberhardt

May 21 9:00AM - 12:00PM

ESB 5104

Thesis Defense

Towards Robust Projections of Glacier Change Across Western Canada: Climate Downscaling, Surface Energy Balance Models, and Neural Networds

PhD Thesis Defense

Speaker: Christina Draeger

Supervised by: Valentina Radic