Machine Learning Modeling for Autism Spectrum Disorder Handling and Treatment

The project is about developing a decision support tool to provide a personalized handling and treatment for Autistic Syndrome Disorder patients. This decision support tool will integrate machine learning modeling that will be used to suggest optimal and personalized guidelines for a very large spectrum of ASD patients, not available so far. Theses guidelines will be used by concerned parents, teachers and therapist that are in charge of these patients. The partner is a company that offer accompanying and training services to ASD patients’ parents and therapists.

Blockchain Enabled Land Registry: Towards Improving Transparency, Accountability & Compliance

The current land registry system in Ontario lacks efficiency and transparency; and is susceptible to information quality problems due to lack of a uniform and integrated system to record and share real-time data about land property transactions across stakeholder organizations. To overcome such issues, many countries are turning to blockchain technology to enable land registration transactions.

Career Stage, Age, and Gender on Employees’ Ethical Challenges: a Canadian Perspective

Corporate employees face a range of ethical pressures and challenges; in some cases, employees fail at these challenges, and the result is often bad for employees, for employers, and for the Canadian public. Ethics education in post-secondary settings and corporate ethics training may help, but needs to be designed in a way that takes account of the specific kinds of challenges and pressures employees actually face. First-hand testimony suggests young people (in their 20s) face special challenges and special risks because of their junior status in the workplace.

Scheduling for Meal-Kit Industry

The partner is experiencing difficulties in finding an efficient solution for planning and scheduling the production in meal processing plants. The challenges involve rapid degradation of fresh food ingredients, a wide variety of products and demand which cannot be predicted in advance. The partner spends a lot of time on tactical management of business activities. During this research, the intern will analyse the current business practices and provide a scientific solution to production planning in the food industry.

Generating realistic customer purchase baskets using Generative Adversarial Networks (GAN)

This project uses the purchase history data from loyalty member cards at the basket level (i.e., all items bought by a customer during a particular trip) for customers under the loyalty program of a chain drug store to develop a model that can generate a realistic future “customer shopping list” (i.e., customer baskets) using the novel machine learning technique of Generative Adversarial Networks (GAN).

The social license to operate: insights from Eeyou Istchee

The rise of local corporate–community conflicts surrounding development projects represents a trend rather than exceptional events, highlighting corporate–community relations as a prominent strategic issue.  Despite the emergence of these issues for businesses, civil society, and governments, we still have a limited understanding of the conditions necessary for building and maintaining good relations over a long period of time and at all stages of a project’s life cycle.

Understanding Jewelry Consumers’ Response to CSR Advertising Messages

The research project will look at the appeals, elements, and themes present in luxury goods advertising and determine how luxury brands can integrate pro-social and empowerment messages into its advertising targeted toward women. This will be examined in the context of jewelry advertising as the partner organization for this project, Hillberg & Berk, is a Canadian jewelry company with the goal to create a purpose-driven international brand to empower women through design.

Customer Lifetime Value Prediction Engine: Neighborhood Link Inference and Conversion Prediction

Canada’s financial services industry faces significant challenges to remain internationally competitive in the rapidly evolving web and big data environments. Scotiabank and its global competitors have as a key priority effective use of a large and growing amount of data to optimize the design and pricing of product offerings, to communicate effectively with clients, and to mitigate risk.

Improving the calculation of reserved deck space

The partner uses a simple formula to estimate the percent of deck space committed on upcoming sailings. The goal of this project is to determine whether the accuracy of this calculation can be improved. The objectives of this project include understanding the data used in the “% full” calculation, conducting a literature review to determine how other ferry operators perform similar calculations, and performing a root cause analysis to understand cancellation behavior. Through this project, the partner organization expects to gain insights into how vessel deck space is utilized.

Economic complexity, value chain network and Québec’s global competitiveness

The purpose of this project is to position Quebec in the global production network and to compute Quebec’s Product Complexity Index (PCI) and Economic Complexity Index (ECI) using Hidalgo and Hausmann (2009) methodology. Based on the rankings of PCI and ECI, we can have a clear understanding of the economic structure of different countries and their hierarchical position in the global production and trade network. Hidalgo and Hausmann (2009) argue that economic growth is related to the intensity and diversity of business activities taking place in geographically bounded regions.