Innovative Projects Realized

Machine Learning-Based Air Gap Prediction for Safe Vessel Passage Under Bridge

The Halifax MacKay Bridge is a critical passage for maritime traffic, requiring accurate air gap predictions to ensure safe vessel clearance. This project will develop a machine learning-based forecasting model that estimates air gap values at 30-minute, 90-minute, and 72–96-hour intervals. Using data from the Port of Halifax, including tide levels, weather conditions, and traffic loads, the project will create an AI model to assist port authorities in decision-making.

DeepSense will provide cloud infrastructure for model training, while OMC International and the Halifax Port Authority will facilitate an operational environment for deployment. The project’s conservative forecasting approach will prioritize safety by ensuring the predicted air gap is never overestimated. This research will enhance maritime safety, benefiting Canada’s shipping industry and the broader transportation sector.

Supporting Savouring and Positive Affect at Work with Personalized AI-Generated Images for Improving Mental Well-being

Workplace wellness programs often fail to improve mental health due to minimal uptake and engagement. Digital tools for mental health support are becoming increasingly popular; however, work programs are typically delivered through in-person formats and focus on more severe forms of support (e.g., offering leaves of absence) which often results in low engagement from the broader worker demographic. This project examines how wellness strategies can be more effectively supported digitally and provide everyday forms of support. It particularly focuses on savouring positive experiences. While photos are a popular method for fostering savouring in everyday life, people do not typically have photos of work contexts. The intern will explore how generative AI can create meaningful and memorable images of work life. They will investigate whether integrating these into everyday work technologies such as calendars can boost positive emotions and motivate the uptake of wellness strategies personalized to daily life. Partner organizations, Calm and Pathverse, are expected to benefit from the research findings by gaining deeper insights into the development of their own health-related apps. The results may also allow for new intervention strategies and feature possibilities that could be integrated into their apps to be accessed by a broader audience.

Realtime AI Scenario Platform

In recent years, the advancement of Artificial Intelligence has revolutionized technology and the way we use and interact with things online. The technology promises to transform how we interact with services, communicate with people, and find data most useful to us. The project focuses on software development to further develop an existing software involved in servicing the communication and education AI space – specifically, interview preparation and presentation preparation. The expected benefit to the partner organization is enhancement & refinement of existing features on the software platform and development of new features which contribute to future growth.

Implementation of CRM Workflow Process Improvement & Expansion

Now that DEAN Financial has implemented a new CRM system, we need to fully utilize its tools to mine data and make better use of our existing client and prospect base. This project proposes that the co-op student assist in data mining our CRM, which currently holds approximately 1,200 clients and over 1,900 prospects. The student will start by learning about the business, financial products, and how to use our systems, including the CRM. As they get comfortable, they’ll take on more advanced tasks, helping with back-office procedures and gaining a better understanding of both admin and advisor roles. A key part of their work will involve researching and gathering missing client and prospect information, organizing it in Excel, and preparing it for upload into the CRM. Working with the Bluroot Support team, the student will help update client data and identify trends or gaps that could reveal new business opportunities. With cleaner, more complete data, the student will assist in targeting specific client segments with tailored marketing campaigns. They’ll help research insurance and investment products and create clear, effective email and text templates to promote these offerings. The goal is to streamline the process from client interest to completed sales, improving both outreach and operational efficiency.

Electrohydrodynamics of Active Chiral Nematics

Our proposal investigates the electrohydrodynamics of active chiral nematics—complex fluids that combine internal activity, chirality, and orientational order. These materials exhibit rich flow behaviors and defect dynamics when subjected to electric fields, making them promising for future applications in soft robotics, microfluidics, and responsive materials. Through computational modeling and theoretical analysis, we aim to uncover how electric fields influence flow instabilities and defect evolution, advancing our understanding of active matter and enabling new control strategies for smart soft systems.

Design and Implementation of the Intelligent Condition Monitoring System for Natural Gas Infrastructure

Gas pipelines play a critical role in delivering natural gas safely to homes and businesses, but failures can lead to serious risks, including gas leaks and service disruptions. This research project aims to develop an advanced AI-powered system for monitoring the condition of gas pipelines. By using machine learning techniques, the system will analyze data from multiple sensors to detect potential faults early, reducing maintenance costs and improving safety. The project, in collaboration with FortisBC, will first test the system on gas pipelines in Vancouver Island before expanding to a broader network. The expected outcome is a reliable, intelligent monitoring solution that enhances pipeline safety, reduces risks, and improves operational efficiency. This innovation will help FortisBC prevent costly failures, ensuring a safer and more resilient gas distribution system.

Immunometabolic basis of interleukin-10 resistance in individuals with obesity

This international research project brings together scientists and students from Canada and Brazil to study how the immune system becomes disrupted in people with obesity and type 2 diabetes—two major chronic diseases. These conditions are linked to ongoing inflammation in the body, which can lead to serious health problems. A hormone-like molecule called interleukin-10 (IL-10) normally helps reduce inflammation, but in people with these diseases, it doesn’t work properly. Researchers believe this may be due to problems with mitochondria—the parts of cells that produce energy and help immune cells function. Two graduate students from Brazil will join researchers at UBC Okanagan to investigate this issue. One will study how IL-10 affects energy production in immune cells, while the other will test whether natural compounds from foods like broccoli and berries can help restore IL-10’s function. The project uses real human samples and advanced lab tools to explore these questions. This collaboration will benefit all institutions involved by sharing knowledge, training students in cutting-edge techniques, and strengthening research partnerships. The findings could lead to new, food-based treatments to reduce inflammation and improve health in people with chronic diseases, while also supporting innovation in Canada’s health and biotech sectors.

Développement de méthodes de diagnostic et de pronostic de maladies neurodégénératives à l’aide de réseaux de neurones par graphe normatifs et explicatifs

Ce projet vise à utiliser l’intelligence artificielle (IA) pour mieux diagnostiquer et suivre l’évolution de la sclérose en plaques (SEP), une maladie du cerveau et de la moelle épinière qui touche plus de 90?000 Canadiens. En analysant des images du cerveau obtenues par IRM, les chercheurs veulent repérer plus précisément les signes de la maladie et prédire son évolution chez chaque patient.

Pour y arriver, le projet combine des données provenant de milliers de personnes, recueillies dans différents hôpitaux et pays. Un outil d’IA spécialisé, appelé réseau de neurones par graphe, sera développé pour analyser ces données complexes de manière claire et compréhensible pour les médecins. Le système pourra aussi expliquer pourquoi une décision a été prise, ce qui est essentiel pour qu’il soit utilisé en milieu clinique.

Developing a cumulative impact assessment for nutrients in the St. Lawrence River

In this proposed research project, we aim to address the question: How have nutrient levels in the St. Lawrence River (SLR) changed in response to historic anthropogenic activity? The project would aim to: 1) describe the changes in phosphorus and nitrogen concentrations over the past >70 years in the section of the SLR between Lake St. Francis and Lake St. Pierre, and 2) develop statistical models to quantify the impact of potential explanatory variables such as land use change, climate and water flow. The intern will conduct a systematic data search and review to identify and acquire all available data for the region. The intern will conduct advanced multivariate statistical analysis to address the key research questions described above. For example, the statistical output will be interpreted to understand spatial and temporal trends in the SLR, including what the key environmental factors are that drive nutrient levels. This research would facilitate new collaborations between Indigenous, academic and non-profit partner organizations to increase effectiveness of monitoring and restoration activities in the region. It would also provide key information for the Kahnawà:ke Environment Protection Office (KEPO) to protect their waters for recreational, subsistence, and cultural use.

Adaptive Adversarial Behavior for Enhanced Player Experience

Explore how adversarial bots can help players to progress in the mastery of the game through RL and player modeling.

Platform Governance and Gendered Misinformation

The Centre for International Governance Innovation (CIGI) is a leading think tank focused on developing policy solutions to address the governance challenges of emerging digital technologies. My proposed research directly supports CIGI’s core areas of digital governance, platform regulation, and misinformation policy by analyzing how extremist and gendered misinformation adapts within the affordances of digital platforms like Reddit and Gab. This project addresses key gaps in understanding how platform structure, moderation, and algorithmic ranking systems influence the persistence of harmful narratives, particularly around feminism and gender equity.
The project offers social and economic value by informing evidence-based policy recommendations to improve platform accountability and digital trust. Findings will support CIGI’s objective to enhance understanding of transformative technologies and their governance implications, both in Canada and internationally. By applying computational methods and feminist digital theory, this research will also help establish analytical standards for studying digital extremism, contributing to the Hub’s mission of preparing the next generation of digital policy leaders. Additionally, I will contribute to the Hub’s public engagement strategy through knowledge mobilization efforts, including briefings, op-eds, and events that translate research into actionable insights for policymakers and the public.

Glycopolymer based Silicon Quantum Dots – Functionalization and Biological evaluation

Silicon quantum dots (SiQDs) are semiconductor nanoparticles with sizes ranging from 1 to 10 nm that show great promise for photonics, microelectronics, and fluorescent bio-imaging considering their ability to fluoresce from blue to near infrared light. In comparison to conventional quantum dots (which can release toxic metals), Si quantum dots are expected to be safer and more stable for use in biomedical engineering applications.
This project aims at functionalization of SiQDs with glycopolymers and evaluate their toxicity in vitro. The study will assess several parameters such as concentration, compositions, sizes and surface charges of the glycofunctionalized nanoparticles and their impact on cellular update and viability. Different cell lines, a range of assays and techniques will be used to assess the internalization of the nanoparticles, their distribution within the cells and their cellular toxicity. The mechanism of uptake of the nanoparticles within cells will also be studied.