This project will support the early development of CORIMA, a new digital platform designed to help ports and other industries improve how different organizations work together to manage safety and risk. The platform is based on research done at Dalhousie University and uses a systems-thinking approach to identify gaps in coordination that can lead to […]

We are developing a specialized AI-driven Clinical Decision Support System (CDSS) for neurology that integrates a large language model with domain-specific tools (such as neuroimaging analysis, EEG interpretation, and up-to-date medical knowledge retrieval). The system serves as an intelligent assistant for neurologists, helping analyze patient data (e.g. MRI scans, EEGs, clinical notes, etc.) and providing […]

We aim to develop and implement a cost-efficient framework for communicating with proprietary generative AI platforms such as ChatGPT. In fact, these provider companies expose their models through an interface that can be accessed via API. However, calling their API will incur a cost considerably based on our request. Basically, smaller models are cheaper than […]

This project focuses on developing advanced bioinks enhanced with tiny filler materials to improve 3D bioprinting for tissue engineering. By creating stronger, more printable, and biologically compatible materials, the project aims to help the partner organization advance regenerative medicine technologies. This will support the development of new personalized medical treatments and open up commercial opportunities […]

Emerging contaminants (ECs) have become a significant environmental concern due to their widespread presence and risks to health and ecosystems. Meanwhile, agricultural waste is also increasing, providing a valuable source for high-value materials. Traditional detection methods are costly, slow, and require specialized equipment and time-consuming laboratory analyses. Electrochemical sensors offer a low-cost, rapid, and sensitive […]

This project focuses on investigating more efficient and simplified approaches for very short-term precipitation forecasting, known as nowcasting. The goal is to evaluate and adapt lightweight machine learning models that can deliver accurate predictions using fewer computational resources. By reviewing existing models, testing their performance, and exploring ways to simplify their architecture without losing accuracy, […]

This project proposes the development of a Physics-Informed Neural Network (PINN) framework for vessel trajectory prediction using Automatic Identification System (AIS) data collected from Canadian maritime regions. The approach integrates discretized kinematic motion equations—specifically Euler, Heun, and midpoint finite difference approximations—into the training of deep learning models to enforce physical consistency. By combining data-driven architectures […]

Nearly half of adults live with at least one of the top ten chronic conditions—such as hypertension, osteoarthritis, or diabetes—and two in five people can expect a cancer diagnosis in their lifetime. These conditions are among the leading causes of morbidity worldwide, significantly reducing quality of life and increasing the risk of mental health challenges […]

Global fish and seafood consumption has increased, leading to large amounts of byproducts from fish markets and processing industries. Currently, the byproducts are used to produce fish meals or dumped into the ocean, causing suffocation and introducing diseases and noxious species. Other potential uses such as bioconversion into biostimulant for agricultural use. Fish are rich […]

This project aims to develop advanced hybrid cooling strategies for electric vehicle (EV) battery systems by integrating turbulence-enhanced flow control with passive air and active liquid cooling methods. Using an unsteady Reynolds-averaged Navier-Stokes k-omega model, the research will investigate the role of turbulence in improving heat dissipation, temperature uniformity, and overall thermal performance. By combining […]

The increasing severity of climate change and glacial pace of emissions reform is requiring the development of new strategies for atmospheric CO2 drawdown. One of the approaches that has been gaining traction is Ocean Alkalinity Enhancement (OAE), a method that increases the physical absorption of atmospheric CO2 into the ocean by dispersing alkaline materials in […]

The project explores the application of physiological sensors in psychology, mental health, and mindfulness by integrating artificial intelligence for emotional classification. It aims to validate a wearable physiological monitoring system, using devices like Fitbit Versa 6 and Emotibit, to predict stress and anxiety levels through machine learning. This initiative is crucial given the prevalence of […]