Innovative Projects Realized

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

29670 Completed Projects

2811
AB
4990
BC
801
MB
663
NL
825
SK
8841
ON
9197
QC
95
PE
568
NB
1088
NS

Projects by Category

Using Natural Language Processing to Detect Dataset Re-use in the Scientific Literature

This research aims to address one of the challenging problems in open science, i.e., how to reliably ensure that authors share all of the datasets, code, protocols, and any new lab materials associated with their articles. The solution will employ state-of-the-art natural language processing techniques to detect sentences where authors describe data collection or the generation of other research outputs and check whether those outputs are publicly shared. This solution can also be applied to detecting code & software, protocols, and lab materials. The authors will know if all the re-used existing resources are appropriately cited in their publication. Thus, the research outcomes will facilitate the research data management, sharing and citation in the research community and support Canada’s digital research infrastructure.

View Full Project Description
Faculty Supervisor:

Zheng Liu

Student:

Partner:

DataSeer

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

The University of British Columbia - Okanagan

Program:

Accelerate

Polymères avancés pour le développement de serres durables

Notre projet de recherche consiste à fabriquer des panneaux rigides et transparents pour concevoir un nouveau modèle de serre ”verte” et intelligente adaptée au climat froid du Québec. En collaboration de partenaires industriels, nous recyclerons les plastiques comme le polyéthylène et le poly(métacrylate de méthyle), plus communément appellé plexiglas, à partir de sources fiables et abondantes (Loto Québec, SAQ, phare de voiture, électroménagers, etc.). Avec des analyses physiques et chimiques dans les laboratoires de génie de l’École de technologie supérieure et de KWI Polymères, nous évaluerons la qualité des plastiques recyclés pour sélectionner la meilleure source pour nos travaux (propreté, pureté). Ensuite, nous modifierons la composition chimique du plastique pour obtenir un nouveau matériel plus durable et performant pour l’élaboration du revêtement de la serre. Notre projet est important pour l’organisme partenaire, LBM AgTech, car il lui permettra de développer un nouveau concept de serre modulable commercialisable pour la culture de fruits et de légumes dans les endroits froids et éloignées. Ce type de serre permettra de résoudre un problème lié à pénurie de denrée dans les déserts alimentaires.

View Full Project Description
Faculty Supervisor:

Claudiane Ouellet-Plamondon

Student:

Partner:

La Boîte Maraîchère;KWI Polymers

Discipline:

Engineering

Sector:

Agriculture; Manufacturing

University:

École de technologie supérieure

Program:

Elevate

Photonic artificial intelligence to support unconditionally secure communications

The next generation of smart Internet services requires a high level of data protection for sensitive information exchanged (e.g., bank transactions, defense operations). The forthcoming advent of accessible quantum computation will put at risk any classical encryption protocols. Unbreakable data protection, against cyberattacks or unauthorized access, can be guaranteed by quantum encryption protocols, such as the quantum key distribution (QKD) technique. However, it is extremely difficult to embed quantum and classical signals together in the same optical fibers, since the presence of noise and other unwanted interactions between the signals. This project will tackle fundamental and technological challenges that prevent the deployment of QKD in large-scale telecommunications, by developing a new device based on photonic artificial intelligence (AI), which will be applied for the automatic optimization of QKD. The results from this project will provide a novel device, which will be a powerful alternative to electronic-based AI approaches, relying on ultra-high-speed and large bandwidths offered by photonics. The project’s goal is aligned with the long-term commercial objectives of our partner organization, Ki3 Photonics, which also aims at the deployment of unconditionally secure communications with groundbreaking technologies compatible with the current telecom networks.

View Full Project Description
Faculty Supervisor:

Roberto Morandotti

Student:

Partner:

Ki3 Photonics

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

Université du Québec : Institut national de la recherche scientifique

Program:

Elevate

CYA.Live

In today’s world, the video chat and conferencing has been a necessary part of overall routine life (both personal and work). Currently, the video chat and broadcast technologies require lots of bandwidth to transmit high quality data. In overall project, we aim to make video transmission data intelligent by using the state-of-the-art AI technology. This will not only reduce the size of video data but will also include the ‘instructions’ to give users creative control of their representations and serve as a segue to the metaverse – the intelligent part.
In this part of the project, we are planning to utilize the state-of-the-art face generating SofGAN neural network that convert the face video data into the compressed, intelligent, and ready-for-transmission data format. At the receiving end, the transmitted instructions will be used to regenerate the transmitted video data. The additional instructions to manipulate the video will provide the useful mechanism to generate the avatars with realistic faces – a must have feature for upcoming metaverse.

View Full Project Description
Faculty Supervisor:

Abdul Bais

Student:

Partner:

Cya Live

Discipline:

Engineering

Sector:

Information and cultural industries

University:

University of Regina

Program:

Accelerate

Hybrid Nanogenerator for Renewable Energy Harvesting from Ocean Waves

To harvest renewable energy from ocean waves, in this research we propose to study innovative triboelectric
nanogenerators, a new type of energy harvesters especially good at converting small-scale mechanical motions
into electricity. Although ocean wave energy is one of the most abundant and widely distributed renewable energy
resources, it has not yet been extensively used due to high cost and inefficiency of typical electromagnetic
generators (e.g., turbines). In comparison, the triboelectric nanogenerators can achieve higher energy conversion
efficiency at small input mechanical amplitude. We will explore to integrate the triboelectric nanogenerator and
piezoelectric harvester together to gain even larger power density. The hybrid nanogenerator prototype is aimed
at coupling the triboelectric and piezoelectric effects to build self-powered ocean sensing systems for the Internetof-
Things applications.

View Full Project Description
Faculty Supervisor:

Lihong Zhang

Student:

Partner:

Offshore Energy Research Association of Nova Scotia

Discipline:

Engineering

Sector:

Mining; Professional, scientific and technical services

University:

Memorial University of Newfoundland

Program:

Accelerate

Engineered clay as a novel phosphorus (P) sorbent

Fort Nelson & its surrounding area have been devastated economically by recent changes to their Gas Industry leaving more than 1000 well sites abandoned and not restored. Currently, the area is looking to explore other natural resources in an attempt to save their livelihoods. A previous MITACs partnership with Mindbody Networks Inc. (2018-2020) revealed several clay deposits distributed throughout the Northern Rockies Regional Municipality (NRRM), are very efficient adsorbents for potential environmental application, which are believed to hold answers to the economic future of the region. The past industrial partner has incorporated a new entity, Cheyne Industries Inc., to further develop these deposits. They have chosen Dr. Kazemian’s research team at UNBC for this project because of their past successful MITACS partnership and because they have experience in the development of similar products and processes based on natural minerals. Furthermore, Kazemian’s lab at UNBC is a unique facility with state-of-the-art analytical instrumentations that are necessary for this project. in this project, we will conduct an in-depth study on the mechanisms involved in phosphate removal by the company’s clay mineral.

View Full Project Description
Faculty Supervisor:

Hossein Kazemian

Student:

Partner:

Cheyne Industries

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Northern British Columbia

Program:

Elevate

Investigation of CO2 adsorption on MOF porous media using artificial intelligence and advanced computational chemistry

The carbon dioxide (CO2) concentration in the atmosphere has been increasing continuously due to human activities such as burning fossil fuels, which causes global climate change. Conventional CO2 capture strategies are practical, but they are costly and only lower the rate of CO2 emissions to the atmosphere. To decrease the global concentration of CO2 in the atmosphere, CO2 should be directly captured from ambient air with novel separation techniques. Metal-organic frameworks (MOFs) are among the efficient alternatives for CO2 capture, especially in direct air capture (DAC) process. They look like sponges with unique abilities – being able to take up, hold, and release molecules from their pores. Synthesizing all possible MOFs in laboratories is complex, expensive, and time-consuming. The proposed project will integrate artificial intelligence and computational chemistry techniques to design and select suitable MOFs and reveal the active mechanisms during CO2 adsorption/desorption. The artificial intelligence will speed up the pre-screening process of the suitable MOFs for each scenario of CO2 capturing among the large databank of hypothetical MOFs for further experimental and/or simulation evaluations. This process will provide the experimentalists with inexpensive and effective strategies by suggesting most efficient MOFs instead of synthesizing numerous available MOFs.

View Full Project Description
Faculty Supervisor:

Sohrab Zendehboudi

Student:

Partner:

Advanced CERT Canada

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Memorial University of Newfoundland

Program:

Elevate

Numerical Simulation for Subsea Ice Interaction Barriers to Energy Development (SIIBED)

The partner organization, C-CORE, conducts medium- and large-scale experiments on ice fracture. The goal is to estimate the mechanical loads involved in the interaction of icebergs and subsea cables/pipelines. While the ice fracture tests provide the most valuable data, numerical models may help estimate the loads at custom geometries and conditions the test apparatus cannot create. In some cases, numerical models can predict unexpected situations and guide future research. The current proposal suggests developing a custom finite element model for the estimation of loads during iceberg-cable interaction. The model will build upon the prior research into applying cohesive zones for fracture simulation.

View Full Project Description
Faculty Supervisor:

Rocky Taylor

Student:

Partner:

C-CORE

Discipline:

Engineering

Sector:

Mining; Professional, scientific and technical services

University:

Memorial University of Newfoundland

Program:

Elevate

Discovery of Novel Inhibitors to Mitigate Morphogen NODAL-mediated Proliferation of Cancer Cells using a Novel Genetically-encoded Bicyclic Peptide Ligand as Reference.

The proposed project will focus on discovering novel drug candidates as a targeted therapy for cancer using computational and synthetic approaches. 48Hour Discovery INC (48HD) aims to build a high-value drug discovery platform for internal drug discovery programs and for clients that provide synthetic molecules with drug-like properties to maximize the success of early drug discovery efforts. 48HD has developed genetically-encoded technologies that accelerate drug discovery to find new and better drug candidates. They provide services in ligand discovery for research networks, academics and the pharmaceutical industry using a patented process. The current project will add a key resource to the 48HD team to help build out a molecular discovery pipeline that provides rapid access to stable and efficacious drug-like molecules for cancer treatment. The success of the proposed project will create new job openings and thus will increase revenue for 48HD and its clients. The majority of 48HD’s clients are internationally based companies and as a result, the revenue generated at 48HD is incremental for the Canadian economy.

View Full Project Description
Faculty Supervisor:

Frederick West

Student:

Partner:

48 Hour DIscovery

Discipline:

Life Sciences

Sector:

Biomanufacturing

University:

University of Alberta

Program:

Elevate

Full Stack Performance Analysis for Multi-tiered Web Applications

The CXN360 service by Ag Exchange Group (https://cxn360.ca) is an online grain marketing service that allows grain buyers to make offers to purchase grain commodities and allows grain growers to make offers to sell grain commodities. CXN360 currently services the Canadian Prairies and Ag Exchange Group plans to extend the service into international markets and system loads are expected to significantly increase. This project performs a full software stack performance analysis to inform our infrastructure growth planning for these new markets. Existing system optimization and system evolution paths will be explored, with future CXN360 R&D efforts guided by the research results.

View Full Project Description
Faculty Supervisor:

Dwight Makaroff;Derek Eager

Student:

Partner:

AG Exchange Group

Discipline:

Computer science

Sector:

Agriculture

University:

University of Saskatchewan

Program:

Accelerate

Multi-QPU quantum algorithms for quantum dynamics simulations

Quantum computers have the potential to perform computational tasks which are impossible to solve on classical computers. One natural application of quantum computing is to use them for predicting how quantum mechanical systems (e.g., models of quantum magnetism or chemical molecules) evolve in time. However, existing quantum computers – so-called noisy intermediate-scale quantum (NISQ) devices – are not yet powerful enough to generally outperform classical computers. Scaling up is possible by connecting multiple quantum processing units (QPUs) together. This approach has a significant drawback: transmitting quantum information from one QPU to the next is necessary but relatively slow. This calls for the design of specialized algorithms that can take advantage of the multi-QPU architecture without straining the communication channels.
In this project, we will design and optimize multi-QPU quantum algorithms for simulating the time evolution of quantum mechanical systems. We will benchmark the degree to which quantum mechanical systems can be represented on NISQ devices that are subject to the hardware constraints that arise from the slow inter-QPU communication channel. We will further determine optimized protocols to implement quantum simulations so that errors in the computation are minimized. Ultimately, we will execute these algorithms on available quantum hardware.

View Full Project Description
Faculty Supervisor:

Dvira Segal

Student:

Partner:

Entangled Networks

Discipline:

Physics

Sector:

Quantum Science

University:

University of Toronto

Program:

Elevate

Process Optimization and Bio-Augmentation of In-Sewer Treatment Strategies for Optimal Wastewater Quality Control And Nutrient Management

Sewage collection systems have long been considered as sanitation and hydraulic infrastructure, i.e., a medium for transporting wastewater to the treatment facility. Therefore, the management focus has been mostly on hydraulic performance and the prevention of particle settling/odor development in pipes. Current research extends beyond sewage conveyance into sites of chemical and biological transformation with the possibility of reducing H2S production while simultaneously modifying the influent wastewater characteristics to mitigate lower discharge limits and achieve reduced operational costs of the wastewater treatment plant. Thus, the optimization of physico-chemical and bio-chemical processes occurring in a collection system will help in achieving optimal management and control of wastewater effluent quality (especially in terms of phosphorus and nitrogen concentrations) and sludge production. Given the diversity of site-specific conditions encounterable in various geographies and flow variability, it is vital to optimize the process dynamically based on real-time measurement to rapidly identify plant-specific optimum conditions and “design” an ideal influent using in-sewer treatment chemistries.

View Full Project Description
Faculty Supervisor:

George Nakhla

Student:

Partner:

USP Technologies

Discipline:

Engineering

Sector:

Administrative and support, waste management and remediation services; Manufacturing; Professional, scientific and technical services; Utilities

University:

The University of Western Ontario

Program:

Elevate

Previous
1…1,3571,3581,3591,3601,3611,3621,363…2,473
Next

Join a thriving innovation ecosystem.

Subscribe to our newsletter now!

Subscribe