Continuous calibration, interpolation and predictive analytics using Machine Learning

The company provides devices to measure quality of curing light used in dental procedures. These devices produce high volume and high velocity data. This data is then used to forecast a future state and to make a well informed business/operation decision according to an expected future state. One of the challenges in application of such technology is to improve prediction accuracy of the forecast. The company has developed prediction models based on physical chemistry that have been very useful to both the vendors and dentists.

Financial Portfolio Reconciliation using Deconstructed Deep Learning

Citco provides financial products and services to hedge funds, private equity and real estate firms, investors, institutional banks, Global 1000 companies, and high net worth individuals in the Netherlands and internationally. The previous research was focused on optimizing operations by automating trade resolution and reducing risk using machine learning. Given its success in matching individual transactions, the proposed project plans to extend the research to overall portfolio management for identifying discrepancies in the portfolio at the end of the trading day.

Understanding Coastal Ecosystem Response to Nature-Based Climate Adaptation Methods in a Cold Climate

The maritime provinces are currently facing questions around how to create more resilient coastal communities in the face of a changing climate, specifically due to impacts of sea level rise and increasing severity and frequency of storm events. One option for adapting to climate change is to move away from hard infrastructure towards softer/greener approaches, such as nature-base adaptation solutions, also known as “building with nature”.

Temporal soft clustering for profiling and predictive analytics in elderly care homes

Nxtgen Care provides monitoring services for elderly care homes across North America. Their product provides detailed analysis in visual formats to understand the resident’s requirements and directing care in that direction. To meet this goal, voluminous data is collected from the various activities of the residents. Through this project, this data is processed and directed in a way to optimize resources for effective scheduling in a timely manner. This is done with the help of advanced Machine Learning (ML) and Artificial Intelligence (AI) techniques.

Identifying leading safety culture improvement practices to drive innovation to assist in the prevention of workplace injuries

When safety critical organizations develop safety culture improvement strategies they are rarely shared widely outside the organization as there is limited benefit in sharing with others. In contrast to healthcare there is not a tradition of publishing safety improvements in journals or professional magazines. When innovations are shared externally, the description is often sanitized and does not contain then challenges encountered and missteps. In addition, consultancy companies provide a large proportion of the widely shared safety innovations, as they wish to promote their services.

Impact Evaluation and Developmental Evaluation Planning with a Community- Based Not-for-Profit Organisation Focussed on Poverty Reduction

The purpose of this project is to assist a community non-profit organisation to build a comprehensive plan to evaluate its poverty reduction initiatives and activities. The agency partners with other non-profit agencies as well as with government partners, other stakeholders, and persons with lived/living experience.

Deep Learning based Real-time Object Recognition and Tracking for Immersive Training and Maintenance Applications

The immersive software market, which includes virtual, augmented and mixed reality, is expected to see tremendous global growth over the next five years as players from all sectors race to identify and capture market opportunities of the technology.
This project investigates into the business and technical aspects of immersive training and maintenance applications by taking various case studies.

Exploring the Determinants for Start-up Success

Start-ups face several challenges throughout in their attempts to position themselves as goods or services providers. In fact, they can fail at different growth stages. Particularly, they terminate operations before their value propositions advance to solidified business models.

Building a Mobile Platform to Identify Factors that Impact Student Success and Mental Health Related to Their Living Arrangements

This research seeks to discover how matching roommates can improve the living experience, academic progress, retention and mental health of students. It would be carried out using automated questionnaires, interviews, focus groups, surveys to extract user information. The research would help build a platform that can successfully match students based on preferences to help them make the right decision in selecting a roommate and achieve the above set goals.

Retail Supply Chain Predictive Analytics

The project aims predict the demand of customers for small and medium size businesses. Forecasting models will be developed analyze historical data to understand patterns and correlations. Machine learning will be applied to determine how the accuracy can be improved over existing statistical methods, such as Fourier Regression Analysis which is commonly used in retail demand chain management. The demand forecasting model will examine customer behavior and the context surrounding that behavior, including upcoming holidays, the weather, or a recent event such as COVID-19.