University of Waterloo

Business Intelligence (BI) refers to computer-based techniques that facilitate the use of information within organizations to make informed decisions and to run operations effectively based on available data. Our goal is the research and development of new BI tools for focused search and retrieval, which will support analysis and decision-making related to energy conservation and management. Such tools will also have wide applicability to business analytics in general.

We will develop algorithms to automatically generate descriptive labels for large collections of web documents. Such labels can be used by companies in order to decide on which web sites they want to place advertisements, or by electronic publishers to categorize media offers. Currently, there doesn't exist any approach that can robustly and automatically label clusters of documents with a level of quality that approaches human labellers.

The consequences of the mismanagement of credit risk and mispricing of structured credit portfolios are notorious. The purpose of this project is to research, develop and implement superior methods for managing credit derivatives, from single name instruments such as credit default swaps to complex structured products, such as mortgage-backed securities and collateralized debt obligations. The algorithms investigated will employ a bottom-up approach, based on realistic modeling of the underlying collateral instruments (e.g. mortgages).

The surveys being developed by government, health and social science organizations have increased in complexity and as a result, the data that is collected is similarly more complicated. Thus, this project focuses on developing new tools to address issues which arise during the analysis of this complex data including longitudinal data, information which is based on a set of repeated observations of an individual, or group of individuals, over time.

Computer algebra systems such as Maple compute using mathematical formulae as well as numbers, mechanizing the mathematics used in education and research labs. This project focuses on the design and implementation of algorithms for these systems. Emphasis is placed on efficiency that allows large and complex problems of the type encountered in industrial settings to be solved. In the past year the team has made major advances in the core tools that are needed to solve these complex problems.

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.

In today’s highly connected world in which data is so easy to collect, search, and transfer, privacy is of increasing importance. Unfortunately, the way most communication happens today - particularly over the Internet - is quite privacy unfriendly. When you send email, use instant messaging, or simply browse the world-wide web, information about you and your actions gets disseminated to diverse parties around the world, and you have little, if any, control over it.