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

Des marchés publics canadiens durables : Analyse des pratiques étrangères pour moderniser le cadre normatif et outiller les acheteurs publics

Un marché public est dit « durable » lorsqu’il arrive à concilier les trois piliers du développement durable (économique, environnemental et social). Au Canada, rien n’oblige les acheteurs publics à imposer des spécifications techniques ou des critères de développement durable (critères environnementaux ou sociaux) dans les appels d’offres. Pourtant, de nombreuses entités dans le monde imposent déjà à leurs acheteurs publics de telles exigences, et ce, depuis de nombreuses années. Le contexte actuel, provoqué par des engagements par le Canada en matière de réduction des émissions des gaz à effet de serre et les investissements gouvernementaux massifs post pandémie, laisse présager une modification prochaine du cadre normatif en la matière. Or, la mécanique peut apparaître complexe et décourager les gouvernements. Il faut d’abord envisager les meilleures manières de rendre les marchés publics durables tout en demeurant licite au regard des accords de libre-échange, en évitant de provoquer une multiplication des appels d’offres infructueux et en s’assurant que le marché est prêt à répondre aux nouvelles exigences environnementales et sociales. De plus, entre autres en raison des enjeux, mais aussi de la haute technicité des critères et spécifications, il faut accompagner les acheteurs publics dans cette transition normative.

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Faculty Supervisor:

Geneviève Dufour;Valériane Thool

Student:

Partner:

Chardi inc.;Association de l’aluminium du Canada

Discipline:

Sociology

Sector:

Manufacturing; Other services (except public administration); Professional, scientific and technical services

University:

Université de Sherbrooke

Program:

Accelerate

Human Health Risk Assessment of Manganese and Inorganic Manganese Compounds and the Application of Categorical Regression in the Quantitative Risk Assessment of Manganese

Risk Sciences International is currently completing a comprehensive risk assessment of the potential human health effects of manganese. This assessment involves a systematic review of the worlds’ literature on epidemiological and toxicological studies of manganese, following which an international expert panel has scored all of the adverse health outcomes identified through this review using a 12-point severity scoring scale. By standardizing diverse health outcomes on a common severity scale it is now possible to conduct a categorical regression analysis of the results of over 200 scientific papers containing relevant dose-response information on manganese. During the course of this MITACS internship, Ms. Milton will assist Senior Scientists at RSI in conducting the detailed categorical regression of this unique comprehensive database on the human health effects of exposure to manganese.

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Faculty Supervisor:

Patrick Farrell

Student:

Partner:

Risk Science International

Discipline:

Mathematics

Sector:

Professional, scientific and technical services; Public administration

University:

Carleton University

Program:

Accelerate

Validation of a soil improvement method using an anionic fluid addition

Anionic fluid additives for soil improvement have a theoretical ability to improve the strength and performance of soils used as base layers in road construction. Current laboratory standards have not been able to validate their benefits, which have been captured in field trials; therefore, this research project aims to develop a novel laboratory testing program that improves on current testing standards by accounting for concepts such as manufacturer soil preparation specifications. By validating the resulting laboratory process, this project will provide the manufacturer technical support going forward when applying an anionic fluid additive to future industry projects.

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Faculty Supervisor:

Nicholas Beier

Student:

Partner:

Rhide Technologies Inc

Discipline:

Engineering

Sector:

Manufacturing

University:

University of Alberta

Program:

Accelerate

Intelligent Unmanned Surface Vehicles with Safe Navigation and Docking in Harsh Marine Environment

Marine Thinking aims at building a thriving business and using cutting edge AI technologies to transform the marine sector, starting in Atlantic Canada. The project is to develop advanced machine learning algorithms for the guidance, navigation and control unit of the USV, to have a safe navigation with hybrid path planning, obstacle avoidance, intelligent robust control subject to wave, current and wind etc., in harsh marine environment. The interns will develop theories and do extensive simulation and experimental studies. The USV with an automatic docking station is designed to facilitate an autonomous system capable of doing underwater surveys with AUVs, patrols and fishery activities. The company will benefit from having well-tested USVs which can safely self-navigate without interventions. The results will help the company to improve their competitiveness and have larger share of the market in marine industry. The Canadian community will benefit from the state-of-the-art research project.

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Faculty Supervisor:

Ya-Jun Pan

Student:

Partner:

Marine Thinking

Discipline:

Engineering

Sector:

Aquaculture and Fishing; Artificial Intelligence; Technology

University:

Dalhousie University

Program:

Accelerate

Agent conversationnel virtuel spécialisé en marketing numérique

Les agents conversationnels (chatbot) sont de plus en plus populaires. On n’a qu’à penser à Google Assistant, Alexa ou Siri. Ces agents utilisent l’apprentissage profond afin de classifier les phrases des utilisateurs et d’en extraire les informations pertinentes. Les modèles derrière ses technologies sont d’habitude entraînés sur des corpus (des bases de données contenant du texte en langage naturel) générique (par exemple, les articles de Wikipédia). Or, si nous voulons créer un agent conversationnel spécialisé, il pourrait être très avantageux d’entraîner ce modèle sur un corpus spécialisé dans un domaine d’intérêt particulier. Pour ce faire, il faudra trouver des méthodes permettant d’entraîner nous-mêmes une architecture de type BERT en diminuant le plus possible les temps de calcul.

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Faculty Supervisor:

Gabriela Nicolescu

Student:

Partner:

Koïos Intelligence Inc

Discipline:

Computer science

Sector:

Social Innovation

University:

Polytechnique Montréal

Program:

Accelerate

Development of Advanced Deep Learning Algorithms for Computer Vision and CAV Applications

Deep learning is nowadays one of the most popular areas in computer science which has shown extraordinary performance and enjoyed wide use in a variety of fields. This research project is aiming at exploring the application of deep learning algorithms in two fields: autonomous driving with 5G networks, and facility maintenance with CT scanning. In the first field, a number of driving scenarios will be simulated and evaluated to understand the performance of deep learning-based algorithms, leveraging 5G to take advantage of quick data transfer and calculations. The goal of the second part is to design and evaluate different deep learning algorithms to develop a software for defects detection in industrial facilities. Research findings and conclusions drawn in this project will aid future research and upgrades in deep learning applications.

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Faculty Supervisor:

Bo Wang

Student:

Partner:

New Vision Systems

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Speech and language technology development for next generation interactive voice services

Automated speech enabled human-computer interfaces have become essential for the competiveness of many Canadian industries. The demand for more natural, simplified, and low cost user interfaces has made voice enabling of telecommunications, automotive, and consumer electronics devices nearly ubiquitous. Commercially available automated intelligent assistants have been developed to guide customers through problem solving scenarios. The demand for high performance in these services has increased the pressure to improve the quality and reduce the costs associated with the underlying speech and language technology. However, research and development in the areas of automatic speech recognition, natural language processing, and dialog systems requires specialized expertise and significant linguistic resources. Nuance Communications is a world leader in providing speech based interactive services and has a substantial presence in Canada. The Telecommunications Group at McGill University is one of the top centers in North America for research in communications and speech and signal processing. TOBECONT’D

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Faculty Supervisor:

Richard Rose;Mark Coates

Student:

Partner:

Nuance Communications Canada Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

McGill University

Program:

Accelerate

Biocrust Propagation and Transplantation on Mine Tailings and Overburden Substrates for Mine Reclamation

This project aims to develop propagation techniques of biocrust species for mine reclamation. Biocrust -which is the community of mosses, lichens, algae, and cyanobacteria-, protects the soil surface from erosive forces, restore nutrient cycling, sequester atmospheric carbon and retains water in its matrix. Its establishment on reclamation sites is therefore very desirable. However, due to their small size, biocrust may not establish quickly unless assisted. The objectives are: 1) to identify greenhouse propagation strategies for biocrust moss and lichens from Gibraltar mine on tailings and overburden substrates and, 2) to determine the effect of fertilizer on moss propagation. STANTEC, NATS nursery and Taseko | Gibraltar Mine, the research partners, will benefit by gaining insights on propagation of diverse moss and lichen species for reclamation. Gibraltar Mine will obtain propagated biocrust mats and a transplantation experiment design to implement filed research on the mine, situated near Williams Lake, BC.

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Faculty Supervisor:

Anayansi Cohen-Fernandez

Student:

Partner:

Stantec Consulting (Sidney, BC);NATS Nursery;Taseko | Gibraltar Mines Ltd

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

British Columbia Institute of Technology

Program:

Accelerate

Applied intelligence for scheduling and dispatching operations in industrial applications

Artificial intelligence (AI) applications are being widely explored in industrial domain. In this project, we will develop an AI workflow for applying reinforcement learning in simulation models. The goal is to add intelligence in scheduling and dispatching tasks. Reinforcement learning (RL) is a sub-field of AI, where computers are trained to make decisions based on the system state. Simulation models are used as a digital environment for RL training. The model captures the physical system behavior and simulates the system changes in response to the RL decisions. The AI workflow in development will ease the embedding of AI in industrial applications.

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Faculty Supervisor:

Soumaya Yacout

Student:

Partner:

SimWell

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Polytechnique Montréal

Program:

Accelerate

Experimental Investigation and Field Monitoring of Geocell- Reinforced Roads under Freeze-Thaw Cycles

Freeze-thaw is a major cause for distress of roads in Canada. This research project is to investigate the use of Neoloy geocells to strengthen the roads to minimize the freeze-thaw damage. A fully instrumented road stretch will be constructed to monitor the long-term performance of the geocell-reinforced roads subjected to seasonal freeze-thaw cycles. Meanwhile, a series of laboratory-scale model tests will be conducted. The outcomes of this project are (1) quantifying the beneficial effect of geocells in reinforcing roads against freeze-thaw damage, (2) understanding the underlying reinforcing mechanisms, and (3) development of relevant design method. The results of this research will contribute to improvement of the design and construction practices of durable roadways in Canada.

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Faculty Supervisor:

Cheng Lin

Student:

Partner:

Stratum Logics

Discipline:

Engineering

Sector:

Construction and infrastructure

University:

University of Victoria

Program:

Accelerate

Investigating the Industrial Green House Gas (GHG) Emissions in the Greater Toronto and Hamilton Area (GTHA)

The Canadian Net-Zero Emissions Accountability Act 2020 has established an ambitious target of achieving net-zero emissions by 2050. Even though the measures stipulated in the Pan-Canadian Framework on Clean Growth and Climate Change have been helping Canada in making significant progress towards its climate action goals, the eventual goal seems distant. The pursuit for the above target needs more granular data to understand the baseline Green House Gas (GHG) data and implement customized mitigation measures for GHG sources. The objective of the proposed research is to investigate industrial GHG emission data in the Greater Toronto and Hamilton Area (GTHA) for increased granularity. This data will be used to enhance the accuracy of the industry GHG emission estimation and avoid double counting. Outcomes of this research will inform planning and implementing mitigatory measures for industrial emittors in the GTHA.

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Faculty Supervisor:

Rajeev Ruparathna;Gyan Chhipi Shrestha

Student:

Partner:

The Atmospheric Fund

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Windsor

Program:

Accelerate

Discovering novel approaches to robust machine learning and visualization for banking applications

The overall objective of this project is to develop approaches to improve rating robustness that are distributionally robust. We will develop techniques to utilize ensemble learning machine learning models with categorical monotonic constraints. Lastly, we will develop novel data visualization tools for business intelligence tasks that will help decision makers at Scotia Bank.

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Faculty Supervisor:

Apurva Narayan;Joan Hu;John Braun;Fatemeh Hendijani Fard;Mohammad Khalad Hasan;Apurva Narayan

Student:

Partner:

Scotiabank

Discipline:

Mathematics

Sector:

Finance and Insurance

University:

Simon Fraser University; The University of British Columbia - Okanagan

Program:

Accelerate

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