Charity donations have long been a feature of society smoothing the differences between rich and poor. In the past these donations were handled manually using a variety of ah hoc means. This continuing project aims at systematizing the donation process by implementing an online system that facilitates the connection between donors and recipients, thus enabling […]

This MITACS BSI project represents a collaboration between Skillsetter.com (an online interpersonal skills training company and Partner Organization) and members of the University of Calgary’s Department of Computer Science (Professor Richard Zaho [Academic Supervisor] and Mohamad Elzhobi [PhD Student and Project Intern]) aimed at developing a machine learning model to classify aspects of judgmentalness from […]

Successfully fabricating complex living tissue structures demands carefully designed tissue scaffolds that mimic complex native tissues, which 3D bioprinting aims to achieve by creating 3D mimics of natural tissues. The fabrication of functional 3D tissues is challenging due to the limitation of oxygen and nutrient transport to cells inside the printed scaffold. Among the numerous […]

The main problem this internship project explores is the selection, conversion, and encoding of mathematical models that pertain to the finance industry for processing on available types of analog optimization processors. This research investigation aims to develop new algorithms and code that take advantage of an analog optimization process which acts as an “oracle” for […]

Current therapies to manage pain either result in side effects or are insufficient and the associated medical costs and loss of work days come pose a tremendous socioeconomic burden. We recently showed that T-type channel activity is aberrantly regulated in inflammatory and neuropathic pain by the deubiquitinase USP5, and we have begun to explore this […]

Pipelines are an imperative part of the energy sector and have a substantial impact on the Canadian environment, and economy. The slightest mishap in pipelines can lead to devasting environmental impacts as well as huge financial consequences. Therefore, developing sound automated pipeline monitoring by leveraging artificial intelligence (AI) and machine learning (ML) for safe and […]

The aim of the EPES (Epilepsy Pre-Evaluation Space) is to create an immersive tool to better understand spatiotemporal phenomena inside epilepsy patients’ brains, by creating a 4D spatial-temporal visualization of electrical activity. Used for pre-surgical evaluation of epilepsy patients suited for surgical resection of the brain region, where seizures onset zone lies. EPES provides an […]

Biohubx supports the life sciences ecosystem in significant ways, but they need a way to visualize that ecosystem and its connections so that they can perform informal traffic control. This project will create a visualization of the life sciences ecosystem in Canada and around the world, and this resource will be used by Biohubx to […]

We have looked into the CSI problem as a two-phase problem in a heterogeneous (matrix, wormhole) porous medium. If the solvent is a light hydrocarbon, this is fine. However, especially with CO2 and DME, mass transfer to and from the aqueous phase is substantial. In this project, we take advantage of our extensive experience in […]

Nearly one in ten people that are hospitalized in Canada develop a complication with sudden loss of kidney function, called acute kidney injury (AKI), which may lead to other severe health problems such as kidney failure requiring dialysis treatment, heart attacks and failure, stroke and even premature death. Discharge from hospital can be a difficult […]

The global pandemic has made it clear that there is an urgent need for high-quality mental health services for children and youth. Right now, quality is measured in terms of the number of visits to clinics, emergency departments, hospitalizations, and the costs associated with those services. The voices of children, youth, and their families are […]

Real-time prediction of incoming turbulence has important practical utility in the control and monitoring of fluid systems. Flow estimation using smart sensing techniques will improve our ability to predict and control these flows. However, current sensor-based flow reconstruction methods have not been tested to effectively resolve multi-scale, chaotic and unsteady turbulent phenomena that are commonly […]