This project seeks to develop GPU based versions of CPU implemented Subsurface scattering shaders. Rendering in video games and movies require increasingly complex simulation of skin and other effects from translucent materials As a visual effects solution provider, Cebus Visual Technology is very interested in implementing their shaders on the GPU to increase the computational […]

In this project, we focus on increasing sales in e-commerce shops by offering purchasing incentives to shoppers who are likely to leave without buying. More specifically, our goal is to predict which shoppers are likely to abandon their shopping cart and what can be done while they’re still on the site to customize their shopping […]

The proposed research project proposes to study how to best provide a student learning portal for children of age 8 to 13 years old. Such system requires to carefully reviewing the literature both in terms of designing for children, and in terms of interpreting the results of usability studies with children. Designing an effective student […]

The proposed research project is intended to develop an educational tool for the general public to be able to perform self-screening of their skin lesions. For this, a melanoma-detection mobile application will be developed to analyze lesion images acquired using a low-cost dermoscope attached to a smartphone. This product helps public or students to learn […]

In medicine, imagining-based exams are used to support diagnostics, treatment planning and/or the treatment itself. Considering the number, integration and nature of devices in a multi-surface environment (e.g. smartphones, tablets, multi-touch surfaces and wall displays), this project proposes a system for imaging visualization and manipulation that takes advantages from each device’s capabilities in the environment. […]

This research project will investigate cost effective methods for agricultural production. Specficially, soil will be classified as high expected yield and high yield variability, high expected yield and low yield variability, low expected yield and high yield variability, and low expected yield and low yield variability using appropriate statistical methods. Different seed and fertilization rates […]

Smartphones are not only incredibly powerful computing devices, but also sophisticated sensor platforms. Leveraging sensed user context, such as location, to provide targeted advertising has been discussed as a potential application of ubiquitous sensing in the literature, and is beginning to appear in industrial applications. In this proposal we describe the innovations necessary to realize […]

The purpose of this research is to develop a solution that uses Artificial Intelligence and Predictive Analytics to Improving the Efficiency in Customer Interactions and Investment Selection.

In many industrial and engineering applications, process control plays a central role. Among the possible control strategies, model predictive control (MPC), also called receding horizon control (RHC), stands out for its excellent ability to handle constraints. While MPC has been successfully applied to many industrial applications, further developments are limited when it becomes necessary to […]

This project will involve using statistical modeling and machine learning techniques in order to identify significant factors that exist in user interaction logs collected from a social gaming system. Next, these factors will be used to inform, implement, and test an adaptive platform for managing and improving behaviors that relate to user experience and/or user […]

The project will attempt to extract useful information from emails as well as attempt to classify emails as meeting intent or not. The proposed project deals with attempting to leverage current machine learning and natural language processing techniques to build a prototype that can solve the above problems. This will benefit the company by not […]

Current procedure for monitoring securities market in Canada relies heavily on tips from outside and hard coded rules and thresholds. This approach leaves many suspicious cases out of investigation (i.e. false negatives). We introduce a data mining approach to identify irregularities in securities market. These irregularities are known as suspicious cases that might be associated […]