Sofia Addab, Jean-Gabriel Lacombe, and Georgia Powell are master’s students in the Department of Experimental Surgery at McGill University in Montréal. During a shared internship shadowing medical staff in the emergency room at the Montreal Children’s Hospital, the trio quickly identified that the time-consuming practice of calculating correct doses of IV medication by hand was leading to potential mistakes and disrupting workflow at critical points during the intake of trauma cases in the hospital’s emergency room, posing serious safety risks to children.
Ananda Devices has developed an innovative technology to produce high-throughput organ-on-chip technology for
commercialization in the pharma industry and cosmetic industry. For cost effective and fast commercializing the device, semi
automation/automation is required for the high throughput data analysis. Further validation of the automation algorithm is
required for data accuracy.
Printed electronics is a fabrication method that allows for the high-volume production of flexible electronic devices, but is limited because it is still too expensive due to the lack of an efficient and effective quality control solution. This project focuses on the transformation of a laboratory-proven quality control method into an industrial-scale prototype product.
Minke whales are common in the North Atlantic, but there are huge gaps in scientific knowledge about the species. Through collaboration with Mériscope, we will attach satellite tags to minke whales that feed in the St Lawrence Estuary (SLE) in the summer to track where they migrate throughout the rest of the year. At the same time, we will collect tissue samples from the SLE minkes, which we will analyze in comparison with minke whales across other parts of the Atlantic.
This project is aimed at understanding evaluating and reviewing gene therapy methodologies used in products in development, assessing the risk and safety and regulatory investigations in different regions of the world. There is limited guidance and regulatory expertise in this area and current drug candidates are being dealt with on a case-by-case basis by the regulatory authorities under existing international guidelines. The intern will aid in furthering this study with assistance from staff and scientists at Charles River labs.
Cognitive AI software using a metallurgy ontology can use semantic network descriptions of mineral deposits and mines to evaluate a mineral deposit and determine which deposit, anywhere in the world, most closely matches its metallurgical characteristics. After finding a suitable match, the user would be able to read the metallurgical report(s) of the similar deposit(s) to compare with their current understanding of the metallurgical considerations of their project.
It is critical for farmers to have cultivars so that they can make decisions on the best practices to undertake when growing a new crop and maintain productivity and competitiveness in the marketplace. Pulse production is growing in demand and is an established market in Canada. In addition, plant based protein products are growing in popularity. We are working on developing a set of tools and information and varieties that will enable farmers to grow more pulses in Quebec. We will also determine basic agronomic parameters that will maximize crop yield and minimize risk of crop failure.
Bats are fascinating animals that provide many ecological services by regulating insect populations. They can eat about 600 insect per hour! Since the introduction of white-nose syndrome in 2006, bat populations in North America have become increasingly threatened. This fungal disease has caused dramatic decreases in many bat populations. Without a cure for white-nose syndrome, the protection of bats and their habitat might be the best way we can help them. However, since bats are small and nocturnal, their preferred habitats are understudied.
ML/AI is widely used and deployed in many industries. Its deployment in Asset Management industry (and
especially in Canadian pension fund sector) is significantly behind. Part of it is the fear of “black box” and what recommendation it gives. This sentiment is outdated as the recent advancements in ML/AI allow looking inside the “black box and thus focus on “white box” asset allocation recommendations.
Another reason is that asset management these days is the intersection of three disciplines: Financial
Economics, Statistics, and Computer Science.
ML/AI is widely used and deployed in many industries. Its deployment in Asset Management industry (and especially in Canadian pension fund sector) is significantly behind. Part of it is the fear of “black box” and what recommendation it gives. This sentiment is outdated as the recent advancements in ML/AI allow looking inside the “black box and thus focus on “white box” asset allocation recommendations.
Another reason is that asset management these days is the intersection of three disciplines: Financial Economics, Statistics, and Computer Science.