Adult onset diabetes, or type 2 diabetes, is becoming more common in Canada and across the world. And it is a risk factor for stroke. For example, silent strokes lesions are common in adults with type 2 diabetes. Despite this knowledge, we do not have a very good understanding as to how type 2 diabetes […]

Patients with coronary artery disease often present clinically with a cluster of vascular risk factors, which predispose them to stroke and can cause subtle deficits in cognitive performance. These deficits are believed to pertain, in part, to disease of the small blood vessels providing blood to the brain. Fitness is associated with better cognitive performance, […]

Given the current global environmental crisis, developing sustainable solutions to enhance or replace our current agricultural practices is critical: the agricultural sector exerts important environmental pressure through its aggressive land, water and pesticide usage combined with the ever increasing demand on food supply. Mitigating this problem requires developing more sustainable and efficient agricultural techniques. Precisely, […]

Preliminary work has shown that adding excess CEACAM1-specific antibody, 26H7, to hela cells expressing carcinoembryonic-antigen-related cell-adhesion moleule (CEACAM) 1-4L decreases CEACAM1-4L in the plasma membrane and shifts their surface expression from a monomer-oligomer mix to mainly monomers. A super resolution microscope will be used to co-localize CEACAM1-4L with 26H7 in order to determine the optimal […]

Assessment of surgical data from an operating room is a complex process that may require significant resources such as expert input and advanced technology. Automation brings a considerable opportunity to greatly reducing these significant resource requirements – e.g., using computer vision software to detect clinically relevant actions during surgery. However, those detections should be interpretable, […]

Heat exchangers, used in building heating, ventilation and air conditioning (HVAC) systems to transfer heat from hot to cold fluids, are designed to operate under ideal conditions. However, in practice operating conditions may vary with ambient temperature or humidity. HVAC system efficiency can be improved significantly if fluid flow rates are adjusted in response to […]

The proposed study aims to address how different social and political climates affects the mental and physical health of transgender and gender diverse people living across 4 U.S. states and 1 Canadian province. This is significant because we are at a turning point in history in which there is both increasing visibility of trans people […]

Delphia’s business model revolves around generating insights for investing firms that allow them to make better trading decisions. It has been shown that detecting when Twitter users post about recent or future purchases has the potential to increase the accuracy of company sales forecasts, which in turn can inform stock trading strategies. This internship project […]

SS&C processes more than 80% of financial scanned and faxed documents in the US and requires large amount of manual labor in order to map information from a document into another form. Advances in neural networks applied to computer vision have produced text detection and recognition that nears human performance. This project will be leveraging […]

The multiple sclerosis (MS) clinic at St. Michael’s Hospital (SMH) is among the largest in the world. While considerable data is collected from the MS clinic in both structured and unstructured form, the ability to glean this information to assess quality of care and conduct advanced analytics such as predictive modeling is limited. In this […]

The goal of this project can be divided into three subobjectives. First, we need to propose, implement and train an accurate eye tracking model on the server, then migrate it to an embedded platform with a simple application that can run the model. Finally, we need to experiment different pruning methods for the network and […]

On time discovery of problems and constant monitoring of construction sites have great economical benefit. It requires the capability of highly efficient and accurate object detection and segmentation algorithms that can work with coarsely labelled training samples. The project is aimed to develop new learning-based object detection and segmentation algorithms for problem detection and mapping […]