Estimating Real-Estate Property Prices and Days on Market through Machine Learning

In collaboration with Western Canada Realty, we aim to develop a real-estate valuation online service for the Alberta real-estate market, especially for Edmonton. The product resembles Trulia and Zillow on a high level, which are real-estate price estimation web services in U.S. The system requires a backend that takes as input house pricing information from several sources including real-estate property assessment publicly available from the City of Edmonton website and recent house transaction records on MLS®.

Intelligent surveillance for event detection

We aim to develop a video surveillance system that detects and reports events of interest to users. Traditional way is to use RGB cameras to operate in constantly and evenly illuminated areas to detect simple events. The challenge is that visual characteristics of an unconstrained scene are unstable due to illumination variations. In this project, by using RGB-D cameras, 3D position information of humans can be obtained, which is robust and insensitive to the illumination variations.

Enhancing Recommendation Engine for Open Source Software with Community Structures and Copulas

In the constantly expanding world of open source software and services, developers find it increasingly difficult to choose open source that is compliant, secure and reliable. There are millions of open source software and services publicly available today, and compliance, security and quality related information is extremely difficult for developers to find, making mindful selection of open source an onerous process.

Variable selection for uplift modeling

Insurance companies heavily fund marketing campaigns such as, for instance, customer retention or cross-sell initiatives. Uplift modeling aims at predicting the causal effect of an action such as medical treatment or a marketing campaign on a particular individual by taking into consideration the response to an action. Typically, the result of an uplift model is used to call customers for marketing some products based on important attributes of a customer.

A container Approach for Isolation in a Multi-Tenant Internet of Things Platform

Internet of Things (IoT) is a topic that many enterprises including Ericsson are pursuing to find innovative ways of providing a better and futuristic service to the clients. The large amount of CapEx and OpEx related to IoT infrastructure deployment and operation and humongous amount of data generated by IoT devices on the edge and in the center demands creative ways of sharing the IoT infrastructure between clients and effective ways of transferring/handling the generated/processed data.

Design and fabrication of transmon qubits

Despite the monumental advances made in classical computing technology over the past decades, computationally expensive tasks are still presenting daunting challenges to researchers and industry. Quantum computing has the potential to revolutionize many facets of information technologies by pushing the frontiers in various fields ranging from machine learning to cryptography. This research project aims at designing and fabricating the fundamental building block of a quantum computer, a qubit, using industry standard nano-fabrication techniques.

Real-time positioning and tracking of goods in long distance transportation trucks

Since the adoption of the North American Free Trade Agreement (NAFTA) signed on January 1st 1994, the amount of truck freight moved between Canada, U.S. and Mexico has increased considerably. However, the transportation of goods has still have some gaps that need to be settled such as loss of merchandise and delay in delivery time. The reason of these gaps is due to the involvement of several participants in the transportation loop. The delivery of products from the manufacturers to the retailers is done through asset based carriers (55%) and owner operators (45%).

Data supervision and security in large data repositories

Ensuring data security in large data repositories is a challenging task as the volume and the nature of the data to secure constantly evolves. Large repositories are mostly composed of documents expressed in natural language and as a result they are a rich source of information. Given the importance of personal data protection, this proposal explores new methods to mine networks of communications between users and detect improper dissemination of sensitive information.

Three-dimensional Object Pose Estimation

Estimating poses of three dimensional (3D) objects is of great importance to many high level tasks such as robotic manipulation, scene interpretation and augmented reality. Detecting poorly textured objects and estimating their 3D pose is still a challenging problem. The objective and expected result of this research is to develop a systematic and applicable approach that could detect poorly textured 3D object pose. The proposed method is using state-of-the art deep learning in computer vision.

Advanced Analytics for Credit Unions

The worldwide data explosion would emphasize on importance of knowledge discovery from massive, heterogeneous, and dynamic volumes of information (Big Data). Similar to other industrial organizations, Credit union industry deals with massive amounts of structured (e.g. customer demographics and transactional data) and unstructured (e.g. email, social media data, comments) data which they have not utilised well to be able to proactively offer their products and services according to their customer needs.