Innovative Projects Realized

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

29670 Completed Projects

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4990
BC
801
MB
663
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825
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8841
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9197
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95
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568
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1088
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Projects by Category

Comment maximiser l’engagement des utilisateurs par l’analyse et les modifications des interfaces et de l’expérience usager ?

Imaginez un monde dans lequel vous seriez les acteurs du contenu audiovisuel. Un monde dans lequel votre avis aurait un réel impact sur vos émissions préférées. Ce projet va dans ce sens puisqu’il tente de créer une réelle connexion entre les diffuseurs et les téléspectateurs.
L’interactivité est donc de mise, tentant de mettre l’utilisateur au centre du processus de création. Ce projet aura un aspect lié à l’ergonomie puisqu’il faudra repérer les critères sur lesquels influer pour rendre le contenu de meilleure qualité. Toutefois, un problème demeure. Celui-ci consistant à changer un contenu de façon directe par rapport aux retours reçus. Ce projet consistera à développer et apporter des modifications pertinentes par rapport aux avis reçus, aux critiques des utilisateurs et des producteurs pour permettre ainsi d’influer, de façon visible, sur le contenu diffusé. Liveshout (initiateur du projet) prévoit pouvoir offrir, au terme de ce projet, un service novateur pouvant faire de leur entreprise un chef de file dans ce secteur d’activités. Tous les utilisateurs auront alors un réel contrôle sur le contenu qu’ils regardent, passant du stade de simple spectateur à celui d’acteur.

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Faculty Supervisor:

Sylvain Hallé

Student:

Partner:

LIVESHOUT

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Université du Québec à Chicoutimi

Program:

Accelerate

Development and Testing of Advanced Energy Recovery Ventilator Geometries

Buildings globally play a substantial role in energy consumption, representing more than 30% of the total energy demand. However, this energy usage is hindered by a lack of efficiency in HVAC systems, insufficient insulation, and the continuous need for fresh air, resulting in approximately 30% of this energy being wasted. Energy Recovery Ventilators (ERVs) play a crucial role in enhancing energy efficiency in HVAC systems in buildings by capturing and transferring heat and moisture from exhaust air streams to pre-condition inlet fresh air. This study aims to enhance the thermal performance of membrane-based ERVs through modifications in channel design.
In this study, experiments will be conducted using an experimental setup at CORE’s company to investigate novel optimized geometries of ERV. Based on numerical simulations, reducing the channel height on one side of a specific CORE product could increase thermal efficiency by up to 5%. It has been numerically observed that in the same geometry which has a corrugated side, introducing a rib in the flow path enhances mixing, leading to increased heat and mass transfer coefficients. There is a potential for an increase of up to 4% in both sensible and latent effectiveness as a result of this

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Faculty Supervisor:

Steven Rogak

Student:

Partner:

CORE Energy Recovery Solutions

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

Short-term streamflow forecasting for the Oldman River

The proposed research project aims to develop accurate and user-friendly models to forecast daily streamflow for the Oldman River in Alberta. This project will involve using advanced machine learning methods, such as Artificial Neural Networks (ANNs), Extreme Gradient Boosting (XGBoost), and Long Short-Term Memory (LSTM), to improve the reliability of streamflow predictions. By enhancing the ability to predict river flow, this research will support better water resource management, including optimizing reservoir operations and flood control. The final outcome will include an interactive web application that automates data collection and updates forecasts in real-time, making it accessible for decision-makers who do not have specialized knowledge.

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Faculty Supervisor:

Evan Davies

Student:

Partner:

Optimal Solutions Ltd

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Alberta

Program:

Accelerate

Identifying Markers of Developmental Competence Using Pluripotent Stem Cell- Derived Blastoids

Currently, embryo implantation success rates in in vitro fertilization (IVF) are low, partly due to subjective and invasive tests. An assay that can quantify embryo potential while preserving its integrity is necessary. Small RNA sequences, microRNAs (miRNAs), are promising, quantifiable, and non-intrusive markers of developmental potential in embryos. Due to ethical concerns with human embryos in research, an alternative model is needed. Recent findings demonstrate the ability of human embryonic stem cells to self-organize into pre-implantation analogues known as blastoids, but it is unknown if blastoids also release development-specific miRNA. We aim to demonstrate blastoids as a model for human embryo potential using miRNAs and ultimately develop an accurate and efficient embryo selection assay. This will improve IVF accessibility, affordability, success rates, and patient satisfaction while reducing operational expenses. Implementing this advanced technology will give the fertility clinic a competitive advantage, enhancing its long-term reputation for trust and credibility.

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Faculty Supervisor:

Dean Betts

Student:

Partner:

London Health Sciences Centre

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology

University:

The University of Western Ontario

Program:

Accelerate

Exploratory Study on Net Zero Carbon Building (NZCB) Designs for Cold Climates – Phase I

The following proposal aims to research and develop Net Zero Carbon sustainable design strategies for a chalet, serving as a pioneering study to inform broader net-zero carbon residential developments in Montreal. It is motivated by Canada’s goal of achieving net-zero greenhouse gas emissions by 2050. One intern will work with PLAPROS INC., under the supervision of professors from Concordia University, to conduct this research in 12 months. The research will combine the life cycle method with multi-objective optimization to identify trade-offs between life cycle carbon emissions (LCCE) and life cycle cost (LCC). It will involve a precedent study, identifying optimal design strategies, and researching advanced technologies and low-carbon materials. The process involves design iterations, modeling, optimization, and evaluation, resulting in a valuable feasibility study and business case report. Through this project, the partner will determine the optimal strategy for the designed net zero carbon chalet (NZCC) within a reasonable LCC and quantify the impact of their products on the LCCE of the NZCC. This project will provide a benchmark for PLAPROS in constructing net-zero carbon buildings (NZCBs) and position it as a leader in sustainable building practices in Canada.

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Faculty Supervisor:

Liangzhu Wang

Student:

Partner:

Plapros Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Concordia University

Program:

Accelerate

Etude in vivo d’une formulation de nanoliposomes fonctionnalisés (chimiquement modifiés) en tant que système de livraison pour la fonction cérébrale

Le vieillissement de la population impose un vrai défi sociétal afin de maintenir la qualité de la vie, l’autonomie, et la productivité de l’individu âgé tout en minimisant les dépenses de santé. L’un des éléments majeurs de ce défi concerne le vieillissement cérébral lié au développement des maladies neurodégénératives, notamment la maladie d’Alzheimer (MA).
Actuellement dans le monde, plus de 50 millions de personnes sont atteintes de la maladie d’Alzheimer. Ce chiffre pourrait atteindre 152 millions d’ici 2050 si aucune solution thérapeutique ou préventive n’a été trouvée.
Dans l’optique de développer une stratégie efficace de prévention, le projet vise étudier in vivo (sur des souris) l’efficacité de nouvelles formulations de nanoliposomes fonctionnalisés (chimiquement modifiés) sur le cerveau. Cette démarche offre une opportunité unique d’approfondir la compréhension des interactions et l’efficacité entre les nanoliposomes fonctionnalisés et le système nerveux central, élargissant ainsi la portée des recherches menées jusqu’à présent.

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Faculty Supervisor:

Mélanie Plourde

Student:

Partner:

Université de Lorraine

Discipline:

Engineering

Sector:

Education

University:

Université de Sherbrooke

Program:

Globalink Research Award

Violacein effects in mice Rho 264.7 cells

Violacein is a molecule naturally produced in some bacteria such as Chromobacterium violaceum. It has been shown that violacein has promising antibiotic, anti-tumor proliferation, anti-leishmanial and anti-fungal properties. Violacein is commercially available. However, it is very expensive. The objective of this proposed research study is to measure the effects of violacein produced by Escherichia coli on mice Rho 264.7 cells. Over a four month period the intern will use biotechnology techniques to accomplish the objective of this project. When this project is finish, there is an expected benefit to Synbiota Inc. as the software tools, as well as storage and management of the associated scientific data were developed and are maintained by Synbiota Inc. Moreover, the reagent kit used to generate the violacein producing E.coli was co-created by Synbiota Inc. and partner Genomikon Inc. Further characterization of the violacein producing E.coli as well as the efficacy of violacein is of importance for quality control metrics and validation that the reagent kit holds value in the research community. The results of this project will be of value for Synbiota Inc. assisting in the development and marketing of the company’s products.

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Faculty Supervisor:

Jeffrey Fillingham

Student:

Partner:

Synbiota

Discipline:

Life Sciences

Sector:

Biotechnology; Life Sciences (not health); Pharmaceuticals

University:

Toronto Metropolitan University

Program:

Accelerate

Machine Learning developer intern working with Financial Services in the private sector to develop and commercialize AI-powered solutions (1)

AltaML builds artificial intelligence (AI)-enabled solutions to business problems. We work with organisations, bringing together their data and domain expertise with our AI expertise, to develop AI solutions that are deployed in their operations. We also commercialize AI-enabled products business via industry-specific ventures, yielding scalability from our investment in the first solution. Competition for tech talent is fierce, and our talent strategy includes a talent accelerator program, designed to rapidly equip highly qualified individuals with hands-on work experience in applied AI while providing partners with continuous and cost-effective development of AI solutions. AltaML’s AI Lab for Government, also known as GovLab, is a talent accelerator for public service professionals, post-secondary students and recent graduates. GovLab.ai’s mission is to set a global example of how to transform the public sector through applied AI, and is designed to encourage the growth of technical and business AI skill sets that are in high demand across Alberta and around the world. The project comprises internships in a variety of technical and business roles within our organization and within our GovLab program. Within the organization, roles include associate machine learning developer, business development associate, communications associate and finance associate. Within GovLab specifically, roles include associate machine learning developer, associate business solutions consultant, and project delivery associate. The difference is mainly that in GovLab, there is a focus on public sector problems, whereas in AltaML overall, we work across sectors.

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Faculty Supervisor:

Carlos Cruz Noguez

Student:

Partner:

AltaML

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Alberta

Program:

Business Strategy Internship

Unconventional quantum annealing in many-body open quantum systems

Quantum computers promise significant advantages in solving complex problems currently intractable for classical computers by leveraging principles of quantum physics such as superposition, entanglement, and tunneling to perform operations on data. One well-known approach to quantum computation is quantum annealing, pioneered by D-Wave Systems Inc., which develops quantum annealing processors to tackle optimization and sampling problems. Recently, D-Wave has advanced its capabilities to perform coherent annealing within short periods of time constrained by the interaction between the processor and the thermal environment. This limited time may not be sufficient to achieve low-energy solutions in a single forward annealing process. In this project, we try to mitigate this shortcoming by iterative or cyclic quantum annealing protocol, a combination of forward and reverse annealings to reduce the residual energy in each cycle. A crucial aspect of this protocol is that coherence within the system is required primarily during a single cycle. Between cycles, the system remains in a deeply glassy phase, where the qubits are frozen. Consequently, cycles can be repeated well beyond the thermal relaxation time without substantial thermal excitation. We use and develop iterative evolution methods with and without biases: the former linked to bang-bang protocol and continuous-time quantum walk, the latter to iterative quantum optimization. We also utilize advanced computational techniques, including tensor network methods and entanglement measures, to further investigate such an open quantum many-body system. This project aims to benefit D-Wave by developing new quantum algorithms that enhance the performance and efficiency of its quantum processors.

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Faculty Supervisor:

Igor Herbut

Student:

Partner:

D-Wave Systems Inc.

Discipline:

Physics

Sector:

Manufacturing; Professional, scientific and technical services

University:

Simon Fraser University

Program:

Elevate

Virtual Home Staging with Generative Artificial Intelligence (GenAI)

This proposal aims to revolutionize the process of virtual home staging by using advanced technology called Generative Artificial Intelligence (GenAI). Traditional staging, which involves professionals arranging furniture and decorations in a home to make it more attractive to buyers, can be expensive and time-consuming. By harnessing GenAI, we can speed up this process and reduce costs significantly. However, current methods lack the ability to remove unwanted objects, replace colors, textures, and styles. This project plans to address these challenges by developing new AI models that can accurately perform these tasks. The goal is to create a virtual home staging system that is not only fast and cost-effective but also produces high-quality results, benefiting users including any homeowners, designers, and real estate agents.

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Faculty Supervisor:

Di Niu

Student:

Partner:

Greentown Homes

Discipline:

Computer science

Sector:

Construction and infrastructure; Real estate and rental and leasing

University:

University of Alberta

Program:

Accelerate

A probabilistic cluster expansion based approach for predicting synergism of mixtures of compounds in treating cancers

Combination therapy has been one of the cornerstones for combating cancers. Even though the survival rate of cancer patients after receiving combination therapy is improved dramatically, there are still many unsolved issues to prevent us from claiming combination therapy is a cure for cancers. Those issues include it does not apply to all types of cancers; there are increased risks of side effects, and it requires long developmental time and huge costs. One approach to resolve these issues is applying multiple-compound multiple-target paradigm directly during discovery processes, which exactly is the backbone of the partner organization’s proprietary drug discovery technology. Yet the technology lacks an appropriate and efficient way to predict the effects of combinations. Therefore, the proposal aims not only to improve this technology but also resolve issues in combination therapy.

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Faculty Supervisor:

Jack Tuszynski

Student:

Partner:

SinoVeda Canada Inc

Discipline:

Physics

Sector:

Agriculture; Manufacturing; Professional, scientific and technical services

University:

University of Alberta

Program:

Elevate

Addressing Endogeneity in count data using a two-stage copula generated regressor approach

This research project addresses a common problem in studying medical data: understanding the true effects of different treatments when the data is not from a controlled experiment. Specifically, we are looking at patients with systemic lupus erythematosus (SLE) and the number of infections they get. Often, traditional methods need special, hard-to-find data to ensure accurate results. Our new method skips this requirement by using advanced statistical techniques to account for unmeasured factors affecting the results. By applying this method to SLE patient data, we aim to see how Glucocorticoid influences infection rates. This research could lead to better treatment strategies, improving patient care. The partner organization will benefit from a practical and widely applicable tool to analyze complex medical data more accurately, even when ideal data conditions are not met.

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Faculty Supervisor:

Hui Xie

Student:

Partner:

Arthritis Research Canada

Discipline:

Mathematics

Sector:

Professional, scientific and technical services

University:

Simon Fraser University

Program:

Accelerate

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