This project aims to build strong collaborations with Indigenous communities across Manitoba to monitor large mammals using camera traps. The goals of this study are to facilitate Indigenous co-management of wildlife with the provincial government in Manitoba and to inform management of declining species, especially moose, with regards to the factors which are driving decreasing population sizes and distributions.

This project is the extension project of the previous Tele-rheumatology project. In the previous project, we have designed and developed three components: hardware platform, which is the capturing device for rheumatoid arthritis patience movements by using both 2D and 3D cameras; the capture system, which is used by general practitioners to control the hardware platform; and the physician portal, which provides all the captured information from patience to rheumatologists for diagnose purpose.

Social Enterprise is a catalyst for social and economic empowerment and inclusion, and has been identified as an innovative opportunity to address workforce challenges and economic sustainability in Southwestern Newfoundland.

The main goal of this research project is to reduce the rate of occurrence of these distresses by designing and developing improved asphalt binder and asphalt mixtures appropriate for St. John’s environmental and loading conditions. The project will develop recommendations on specifications for asphalt binders, modifiers and asphalt mixtures to enhance the rutting and moisture resistance of pavement.

Risk analysis has a primary role in safety-critical industries such as oil and gas explorations, marine and pipeline transportations, and downstream operations. This essential task is facing a series of challenges due to the increased complexity and volume of generated data. Due to the recent advancements in cloud computing power provided by the two giants: Google and Amazon, a powerful web-platform for advanced risk analytics and predictions is currently under development. SRCube Technologies Inc.

This project aims to validate and explore the application of tailored polymeric materials developed in the department of chemistry at Memorial University of Newfoundland (MUN) for chemical analysis. The main application of such material is in the sample preparation and reducing the workload in laboratories. The materials will be used to treat the various samples such as water (i.e., drinking, river, and sea water) food, and biological samples.

This project is a cooperation between the university and an industrial partner. The project is reflecting the most challenging concerns in the carbon capture processes at the industrial operations. The project seeks possible solutions for the improvement of solvent-based post combustion CO2 capture process. The process improvement qualifiers are the amount of the energy utilization, CO2 absorption, and the solvent selection, which have the greatest operational advantages along with the least environmental impact.

The main aim of this research project is to develop and test a sustainable green remediation technology to bring down the contaminant levels in a hydrocarbon and heavy metal contaminated site so that it can be used for public use. Anthropogenic industrial activities can lead to accumulation of harmful hydrocarbons and heavy metals in soil environment which can have human health impact and may enter food chain affecting ecosystem as well.

In this project, a collaboration between an industry partner and Memorial University will begin with a PDF working on a project partly funded by MITACS and in part by the industry partner. In this project, we will be investigating how to separate oil contaminations from water using filtration through a membrane. The membrane properties will be changed so that the process will be optimized. The oil contamination could be in the finely-dispersed form (i.e. emulsion) or in a mixture form.

Business to Consumer (B2C) market is facing rising complexities in customer acquisition, retention, and engagement, particularly in dealing with younger generations. One of the primary causes of this problem is the significant changes in consumers' behavior and their developing habits that differ from those of the older generations. This project develops an AI-driven behavior recognition platform that recognizes the decisions that are driven by the subconscious mind.