Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

30156 Completed Projects

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812
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842
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8957
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1120
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Projects by Category

Infectious reovirus rescue from temperature-sensitive (ts) mutants

Globally, viruses cause more than half of deaths recorded in humans. Thus, lots of scientific research is ongoing to prevent viral-related disease and death. In addition to known harmful effects that viruses can have, other research has shown that viruses may be beneficial. For example, mammalian reoviruses can destroy certain types of cancer cells without apparently harming normal non-cancerous cells. It appears that some aspects of internal cell signaling play roles in whether or not the virus can kill cells, but virus characteristics that determine cell killing are not as well known. The student will learn a technique called “Reverse Genetics” to make changes in the virus genome in order to define some of these virus characteristics. As a learning experience, the student will determine which of 3 known amino acid alterations in a specific virus temperature-sensitive mutant are responsible for the mutant characteristic, by systematically changing each of the 3 amino acids and testing temperature sensitivity of each clone. For completeness, the student will also make and test each possible double-and triple-mutant, for a total of 8 clones (1 wild-type; 1 mutant; 3 single- and 3 double-mutants).

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Faculty Supervisor:

Kevin Coombs

Student:

Partner:

University of Pittsburgh

Discipline:

Life Sciences

Sector:

Education

University:

University of Manitoba

Program:

Globalink Research Award

Real-time visual detection for robotic inspection

The project aims to equip Hydro-Québec’s current and future fleet of inspection robots with autonomous inspection capabilities. The three main objectives of the project are:
1. Leverage breakthroughs in artificial intelligence to enable robotic vehicles to realize real-time automated visual inspection of the company’s infrastructure.
2. Facilitate and accelerate deep neural network (DNNs) machine learning through visual simulation and synthetic images.
3. Use a simply and securely deployable robotic vehicle to perform the company’s first fully autonomous power line components inspection missio

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Faculty Supervisor:

Yoshua Bengio

Student:

Partner:

Hydro-Quebec (Varennes, QC)

Discipline:

Computer science

Sector:

Utilities

University:

Université de Montréal

Program:

Accelerate

Musculoskeletal disease in a population of cattle admited at the CHUV of the Université de Montréal

1-Currently, cows can be “locomotion scored”. These scores include a category for ‘imperfect locomotion’ or ‘uneven gait’ to define a cow that is unsound (favoring one leg) but not clinically lame. However, this detection method does not discriminate whether locomotion originate from the foot or the leg. Claw lesions are easily diagnosed in a trimming chute. Other orthopedic lesions are more difficult to diagnose. It needs a special clinical expertise and specific diagnostic methods like radiographic images, arthrocentesis and ultrasound. I expect to improve my proficiency in the diagnostic of orthopedic diseases as well as getting familiar with their treatment.
2-Digital dermatitis (DD) is a painful disease that is widespread worldwide. The DD is classified in 5 “M” stages (M for Mortellaro) corresponding to the dynamic of the disease. The M2 stage is a typical painful ulceration between the heels of the hind feet engendering a significant lameness. However, there is still controversy on the level of pain experienced by cows with the other DD stages (M1, M3, M4, M4.1). We would like to better characterize the lameness and the pain perception of all stages of DD in dairy cattle in tie stall and free stall barns. TO BE CON’T

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Faculty Supervisor:

André Desrochers

Student:

Partner:

University of Padua

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology; Agriculture and Food; Other

University:

Université de Montréal

Program:

Globalink Research Award

OPTIMIZATION FOR BUSINESS SYSTEMS AND CONVERSATIONAL ANALYTICS (Retail Personal Store Manager)

State-of-the-art forecasting: Demand planning is a critical part of a business’ operations. Traditional approaches to forecasting use statistical methods to predict future demand from past transactions, but do not take into account contextual data. However, there are good reasons to believe that contextual data – such as weather, events, product descriptions, sentiment analysis (from reviews, Zendesk tickets, social media), and more – can contribute significant signals that directly influence forecasting accuracy for the better. Additionally, a common problem in demand forecasting is new products introduction since there is no historical data on which to base statistical predictions. Contextual data of related products, as well as their sales history, could be used to infer demand for items sharing similar features.

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Faculty Supervisor:

Yoshua Bengio

Student:

Partner:

Enkidoo Technologies Inc

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services; Transportation and warehousing

University:

Université de Montréal

Program:

Accelerate

Modelling the Dependence between Loss Frequency and Loss Rate

Lending to various companies and individuals is a core business of banks. This lending activity comes with credit risk, namely the risk that some borrowers default and fail to make required payments. Estimating credit risk accurately is important for banks’ risk management. In this project, we analyze and model the dependence between loss frequency and loss rate of defaulting customers. The reason for the dependence comes from the underlying economic cycle: in an economic downturn, losses occur both more frequently and more severely than in an economic boom. In this project, we plan to develop a suitable model for this dependence structure between loss frequency and loss rate, which will help estimate credit risk more accurately and thus determine capital requirements more precisely.

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Faculty Supervisor:

Christoph Frei

Student:

Partner:

Canadian Western Bank

Discipline:

Mathematics

Sector:

Finance and Insurance

University:

University of Alberta

Program:

Accelerate

Floating Wetland Treatments to Enhance Remediation (FLOWTER) Project

The IISD-Experimental Lakes Area is currently examining the effectiveness of minimally invasive shoreline methods for cleaning spilled oil. Non-invasive methods are needed to eliminate disturbance to sensitive riparian areas that occur with typical cleanup operations. Non-invasive methods protect sensitive shoreline habitats by minimizing physical contact and they can also speed oil removal after a spill and restore ecosystems more effectively. This project specifically seeks to enhance the capacity of naturally occurring microorganisms to degrade oil by optimizing the application of Engineered Floating Wetlands (EFWs) in near shore environments. Optimizing the effectiveness of this approach provides a real-world, genomics-enabled solution to a potential ecosystem threat that may be superior to other minimally invasive oil spill remediation methods being tested by the IISD-ELA program (i.e. shoreline washing, Monitored Natural Recovery, nutrient addition). TO BE CONT’D

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Faculty Supervisor:

David B Levin;Mark Hanson;Valerie Langlois

Student:

Partner:

IISD Experimental Lakes Area Inc

Discipline:

Earth science

Sector:

Professional, scientific and technical services

University:

University of Manitoba

Program:

Accelerate

Efficient algorithms and software for eye tracking on an embedded platform such as a smartphone

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 possibly explore new approaches in order to improve energy efficiency while preserving other performance metrics of the model such as frame per second and accuracy. The focus of the project will be the third subobjective. Throughout the project, various network pruning methods will be explored and incorporated into the model. Some existing approaches are found in literature. This includes energy-aware pruning and layer-by-layer pruning. TO BE CONT’D

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Faculty Supervisor:

Deepa Kundur

Student:

Partner:

Massachusetts Institute of Technology

Discipline:

Engineering

Sector:

Education

University:

University of Toronto

Program:

Globalink Research Award

Optimizing Gastric Banding Surgery Outcomes in Obese Patients

The negative effects of obesity on quality of life, daily functioning and overall health are well documented. Specifically, obesity is associated with increased morbidity and mortality. Despite this knowledge, the incidence of obesity continues to increase exponentially leading some, generally extreme cases, to seek out laparascopic adjustable gastric banding (LAGB), as a means to control life-long obesity. Although LAGB can be successful, its long-term success is dependent on collaborative, individualized behavioural interventions. This research, a unique collaboration between academics and industry, seeks to develop a multi-factorial assessment/screening tool that may better predict and optimize success of the LAGB procedure.

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Faculty Supervisor:

Gareth Jones

Student:

Partner:

Kelowna Band Surgery – Kluftinger Surgical Inc

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology

University:

The University of British Columbia

Program:

Accelerate

Tightly-coupled Visual-Inertial-LiDAR SLAM

Since Amazon robotics expanded the use of drones to package deliveries to customers, drone applications have been expanded to many industries along with its ability to perform various tasks autonomously. The fundamental technology of drones’ autonomy comes from perceiving its surrounding, creating its own map based on onboard sensors and estimate its location within the map. This technology, also known as Simultaneous Localization and Mapping (SLAM), has been on the rise especially in mining and construction industries for surveying and mapping the site more efficiently; thus, many research works have been performed to improve robot’s SLAM technology. Although various sensor suites have been researched to improve SLAM performance, this project focuses on the novel contribution of developing a robust and accurate 3D SLAM by jointly optimizing stereo cameras, IMU and LiDAR measurements. TO BE CONT’D

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Faculty Supervisor:

James Richard Forbes;David Meger

Student:

Partner:

ARA Robotique

Discipline:

Engineering

Sector:

Aerospace; Technology; Other

University:

McGill University

Program:

Accelerate

Privacy Guarantees and Risk Identification: Statistical Framework and Methodology

A risk-based approach to anonymization includes an assessment of the risk that an attack to reveal or uncover personal information will be realized, known as threat modelling, against the risk that an attack on the data will be successful (e.g., a re-identification). We wish to incorporate the provable guarantees of differential privacy into this assessment of risk, to produce safe data in context of the environment in which it will be used. We also need adapt the methods of statistical disclosure control to such an updated approach.

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Faculty Supervisor:

Rafal Kulik

Student:

Partner:

Privacy Analytics

Discipline:

Mathematics

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Ottawa

Program:

Accelerate

Design of the next-generation of content-based, context-aware product recommender systems

We are in the process of creating and growing a team of researchers expert in the field of machine learning and data-mining. Ultimately, our aim is to create solutions to eliminate the need to manually define personalization strategies. We are working with more than 1000 retail locations across North America and collecting large-scale datasets of customer behaviour. Through a data-sharing/consulting partnership we plan to perform research on the design of recommender systems and predictive models customized for the datasets available to retailers. These methods can be used in their physical and online marketing programs as well as in their dynamical promotions/pricing strategies.

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Faculty Supervisor:

Jiannan Wang

Student:

Partner:

FIND Innovation Labs Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Simon Fraser University

Program:

Accelerate

Investigation of the effects of whole hemp seed dietary supplementation on the microbiome-endocannabinoidome axis and its implications in diet induced obesity

Nowadays, the balance of omega-3 and omega-6 fatty acids (FAs) has shifted in favour of the latter and fiber consumption has decreased, both of which are associated with poor cardiometabolic health. Omega 3 FAs and fiber may impart their health benefits by modulating the endocannabinoid system (ECS) and the gut microbiome, both of which are key regulators of cardiometabolic health and obesity. Whole hemp seeds possess excellent nutritional value; rich in omega-3 FAs, fibers, proteins and vitamins and minerals. Therefore, dietary hempseed may be able to improve cardio-metabolic health by modifying the gut microbiome and ECS. Nature’s Decision is a Canadian hemp producer that pays particular attention to the quality of their hempseeds, and are keen on understanding on their potential cardiometabolic health benefits. TO BE CONT’D

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Faculty Supervisor:

Cristoforo Silvestri

Student:

Partner:

Natures Decision

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

Université Laval

Program:

Accelerate

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