Optimization of Maintenance Planning for a Fleet of Commercial Aircraft in Collaboration with Bombardier Aerospace
Postdoctoral fellow: Dr. Nima Safaei, Mechanical and Industrial Engineering, University of Toronto
Lead faculty member: Dr. Andrew K.S. Jardine, Mechanical and Industrial Engineering, University of Toronto
The research is aimed at providing effective long-term resource planning to effective scheduling of the maintenance tasks over a short-term horizon. The Bombardier Company provides the necessary requirements to the customers around the world to do the predefined maintenance tasks as well as unexpected repair jobs for their aircraft fleet. These services are performed as onsite or offsite, i.e., different centres or stations.
[url=mailto:email@example.com]Dr. Jean-Marie Dufour[/url] , Université de Montréal
This project deals with the mathematics of risk modeling and resource management. Using mathematical and statistical methods, the team develops new tools to help the financial services industry make better decisions about when to trade and at what price based on the available financial data. During the past year, the team focused on the development of statistical methods for measuring volatility and assessing asset pricing models in financial markets.
[url=http://www.lacaisse.com/]Caisse de dépôt et placement du Québec[/url]
Dr. Mike Kouritzin , (University of Alberta)
This project uses mathematical filtering theory to develop computer tractable real time solutions for incomplete, corrupted information problems. These techniques have proven to be beneficial in defence, communications, media effects, and manufacturing. In 2002-2003, Optovation Inc. was added as a new partner, Lockheed Martin Corp. filed for two new patents and we formed a spin-off company, Random Knowledge Inc. to commercialize our technology in the areas of Network Security, Fraud Detection, and Finance.
Dr. Steven Easterbrook, (University of Toronto)
Bell Canada University Labs,
IBM Canada for Advanced Studies
Dr. Changbao Wu, University of Waterloo
Due to the explosive growth in the technology for manufacturing integrated circuits, modern chips contain millions of transistors. Using sophisticated optimization algorithms, it is possible to achieve notable increases in the performance of the chips, reduce the manufacturing costs, and produce faster, cheaper computing for society. Thus, the objective of this project is to enhance the solution of large-scale optimization problems arising in these applications.
Dr. George Karakostas , (McMaster University)
Game Theory studies the phenomena occurring when independent, autonomous entities, called agents or users, act selfishly; game theoretic techniques are now being used to model and analyze networks. This project aims to develop a more realistic modelling of communication and data networks of selfish users using game-theoretic models, study the effects that selfish behaviour has on the overall network performance, and the designs of networks which prevent the rapid degradation of the performance due to such behaviour.
Dr. Barry Sanders, University of Calgary
As the size of computer components approaches the atomic scale, quantum technologies will be necessary for the storing and processing of information. The ability to exploit quantum mechanics opens up a whole new mode of computation that may allow computations previously thought infeasible or impossible. Thus, this project team is working to develop novel systems and techniques for information processing, transmission and security by exploiting the properties of quantum mechanical operations.
A Graphical Modeling Framework to Study Complex Dependence Patterns in High-Dimensional Biological Data
[url=mailto:firstname.lastname@example.org]Dr. Laurent Briollais[/url] , University of Toronto
Graphical models have been one of the most efficient statistical tools used in the last twenty years for the analysis of complex structured high-dimensional data. Graphical models provide a probabilistic framework for making inference and representing the knowledge that we have about these complex structured data. In biological research and more particularly in the emerging -omics disciplines such as genomics, proteomics, metabolomics, transcriptomics, data are often generated from complex high throughput experiments and from complex experimental designs.
[url=http://www.genizon.com/]Genizon Biosciences Inc.[/url]
[url=http://www.tgen.org/]Translational Genomics Research Institute[/url]