The intern, along with his collaborator will explore both theoretically and empirically models of influence over social networks, recommendation systems of online content for users in social networks. Additionally, the intern will study various different ways to cluster and group the content of networks such as Twitter in an automated fashion. Additionally, the intern plans to study various different algorithmic problem the pertain to information retrieval and online content.
This project involves the optimal aerodynamic design of unmanned aerial vehicles (UAVs), making use of stateoftheart computational fluid dynamics and aerodynamic shape optimization techniques. The algorithm development will focus on modeling and exploiting laminarturbulent transition in the optimization cycle. The project should result in new and significantly improved aerodynamic shape optimization tools. This has the potential to lead to new lowdrag and high endurance UAV systems.
The proposed study is a part of a project that will aid in implementing an environmentally clean technology for the recovery of Ni, Co and Cu from slags (waste and semi-waste materials) of nickel production in Ontario. The conventional technology for metal recovery can treat only slags with a high content of valuable metals (~3%), and it results in technological and environmental complications, such as recycling of impurities as well as uncontrollable release of fugitive sulphur dioxide into the atmosphere.