Young vision science graduate helps advance inclusive technology

Nathalie Gingras-Royer, a master’s graduate in vision sciences from Université de Montréal, is working on the development of an inclusive technology that will address the needs of people with visual impairment. As part of her master’s, she took part in the Mitacs Accelerate program to carry out an internship with VMWare, a company that provides virtualisation and cloud computing software and services. 

From humanitarian crises to pandemics: technology to the rescue

Who could have foreseen that humanitarian activities during the 2010 earthquake in Haiti would, 10 years later, guide the way for researchers, entrepreneurs and Mitacs interns during the COVID-19 crisis?

During his deployment at a Red Cross field hospital after the earthquake, Dr. Abdo Shabah saw the potential for greater use of technology in emergency health interventions.

Intern works to protect IP for COVID-19 vaccine development

According to the Public Health Agency of Canada, the total number of COVID-19 cases reached a high of 71,486 as of May 13, 2020 — with Ontario and Quebec collectively accounting for 83% of all cases and 92% of the Canadian death toll. With a mortality rate of 3.4%, COVID-19 has created an unprecedented — and growing — demand for a vaccine.

Québec__Université de Montréal

No additional funding contribution is required from the academic supervisor or university.
Fellowships will be awarded competitively.

Implementation of risk minimization measures and trends over time in the frequency of outcomes

Opioid-related harms such as abuse, misuse, addiction, diversion and overdose have been rising exponentially, a phenomenon referred to as the opioid epidemic. The current research will examine federal and provincial risk minimization measures (RMMs) regarding the opioid epidemic starting in 2016. We will develop a landscape of federal and provincial opioid RMMs, describe trends over time in the number and types of RMMs, assess the association between RMMs and public awareness and the association between RMMs and opioid-related harms.

Reinforcement Learning for Aviation Training

This project seeks to explore the use of a class of artificial intelligence algorithms called reinforcement learning for the purpose of aiding the training of new pilots. In the process, we seek to “teach” an algorithm how to fly an aircraft by exposing the AI pilot to a virtual environment and providing it with flight data and a goal. Alternatively, the algorithm could learn by observing human pilots.

Unsupervised Learning of 3D Scenes from Images using a View-based Representation

We’d like to address the issue of 3D reconstruction from 2D images. This means developing a machine learning algorithm that can take a regular photo as an input and generate a full 3-dimensional reconstruction of the contents of the photo. Such technology can be used creatively or to help the coming generation of robots better understand their surroundings.

Optimization and GMP (Good Manufacturing Practices) translation of GLIDE (Guided Lymphocyte Immunopeptide Derived Expansion) manufacturing process

Leukemia, lymphoma and other forms of blood cancers are still largely diagnosed every year in Canada. These diseases constitute the second leading cause of cancer related death in young adults and the sixth in adult. The five-year survival rates still range between 42% and 85%. Currently, the main treatment is a stem cell transplantation which unfortunately do not prevent lethal relapse. The goal of this study is to develop and improve a novel cellular therapy aiming to limit and prevent relapse of hematological malignancies.

User-friendly app for gauging autism

Autism spectrum disorder refers to a broad range of conditions characterized by challenges with social skills, repetitive behaviours, speech, and nonverbal communication. This once misunderstood disorder affects a broad range of communications skills and behaviours.

According to Public Health Agency Canada, one in 66 Canadian children are diagnosed with autism.

Predicting Scleral Lens Rotation Based on Corneoscleral Toricity

Patients with corneal disease often require treatment with scleral lenses. Unlike regular soft contact lenses, these lenses are much larger and have a space between the cornea and the lens that is filled with fluid before lens application. These lenses are extremely useful in cases of extremely ocular dryness and in patients with irregular corneas. Adjusting these lenses to perfectly mold the surface of the eye is of the utmost importance to ensure that the patient is comfortable and sees well with their lenses.

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