Projets novateurs réalisés

Explorez des milliers de projets réussis issus de la collaboration entre organisations et talents postsecondaires.

30 508 projets complétés

2882
AB
5105
C.-B.
825
MB
681
NL
860
SK
9051
ON
9491
QC
97
PE
586
NB
1141
NS

Projets par catégorie

Multilingual B2B Supplier Detection and Information Extraction

At Tealbook, we search the web to make the world’s business-to-business supplier websites readily accessible. We extract important sentences and keywords to create a searchable database that buyers can then use to find the right supplier for their needs. But right now, we are limited to servicing English-language organizations. Can we expand our services to French? To German? To Korean? To any of the other 7000 languages in the world? Doing so would not only allow Tealbook to reach a wider audience, but also help the world stay interconnected in any language.

Voir la description complète du projet
Superviseur du corps professoral :

Gerald Penn

Étudiant :

Partenaire :

Tealbook

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

A smart edge computing infrastructure to support workflows, communication and logistic in COVID-19 healthcare facilities

The ability of the health system to manage a massive influx of patients is based on the combination of four factors: the personnel, the equipment, the physical spaces and the system in place. A combination better known in jargon as the 4 “S” (staff, stuff, structure / space, system). A fifth factor that is often misunderstood is synchronicity. With great adaptation to the workspace and team structures, a newly trained staff with new equipment, and a system of critical processes that evolve according to the evolution of the environment and the healthcare system status, synchronicity is essential. This synchronicity requires real time data and automations to enable already pressured teams and a stressed healthcare organization to adapt to unforeseen requests and needs.
In the actual project, we present a real time management system designed to empower healthcare systems and workers in the logistical chain of operation under a turbulent environment. This project will significantly help our organization to timely develop a more efficient and scalable C4 solution, capable of offering a wider range of OTT-services to medical personnel and, ultimately, save lives.

Voir la description complète du projet
Superviseur du corps professoral :

Esma Aimeur;Gabriela Nicolescu;Sofiane Achiche;Maxime Raison;Maxime Raison;Sofiane Achiche;Gabriela Nicolescu

Étudiant :

Partenaire :

Humanitas Solutions

Discipline :

Computer science

Secteur :

Health and Related Sciences & Technology; Information and cultural industries; Professional, scientific and technical services

Université :

Polytechnique Montréal; Université de Montréal

Programme :

Accelerate

Using NLP models to fetch SQL data via voice command for SOTI SNAP Analytics (NL-to-SQL)

This project is focusing on creating an integration of a database and mathematical calculation, with the use of Alexa, Google home, Cortana, so that users can use Natural Language to aggregate meaningful data and answer questions from a given database. For example, suppose there is a database about car sales. If I asked Siri, “who is the best sales for BMW in Toronto?” Our designed algorithm should return the name of the top sales from this given database. The project also builds out an Analytics Engine that will perform mathematical calculations on the data submitted by the SNAP APP dynamically.

Voir la description complète du projet
Superviseur du corps professoral :

Gerald Penn

Étudiant :

Partenaire :

SOTI Inc

Discipline :

Computer science

Secteur :

Information and cultural industries; Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

Designing ‘Zero credit touch’ (ZCT) pre-approved credit underwriting program for retail customers

ICICI Bank has developed various ‘Zero credit touch’ (ZCT) strategies where without any credit intervention and additional information taken from customers, credit facilities can be provided. But there are several challenges in the expansion of ZCT strategies, namely, (i) current credit models which are a combination of business rules, scorecards and machine learning models, do not qualify a significant proportion of existing ICICI Bank customers; (ii) wherever customers do not have a salary account with the Bank, estimated income is lower leading to the customer being offered an amount lower than his/her requirement; (iii) customers with fraudulent intentions can open accounts and over time, these profiles would qualify for ZCT. To tackle these problems, we propose a novel ZCT system incorporating several state-of-the-art methodologies to build one go-to product to reduce credit and operations cost of lending whilst providing a superior customer experience.

Voir la description complète du projet
Superviseur du corps professoral :

Sebastian Jaimungal

Étudiant :

Partenaire :

ICICI Bank Canada

Discipline :

Computer science

Secteur :

Finance and Insurance

Université :

University of Toronto

Programme :

Accelerate

Learning Discussion Thread Representations to Empower Content-based Recommendation

VerticalScope is a company that owns online forums in many domains, such as automotive, health, technology, and powersports. VerticalScope uses a content based recommender system to mitigate the cold start problem, where a large portion of traffic on the forums are made by unregistered users. The goal of this project is to learn representations of discussion threads. Thread representations that capture semantic and contextual information can improve the recommender system to suggest more relevant threads to users, and boosts search engine optimization and user retention rate. Understanding user sentiments also allows for the discovery of trending topics, and personalized homepage and advertisements.
Learning thread representations has various challenges. Within the automotive forums for example, there may be multiple threads talking about buying and selling cars. However, though these threads may have similar context, the object of discussion (e.g. the specific car model) can be different, and the learned representations should capture these differences. Another related problem is that there are many out of vocabulary words that may be very important to the relevancy between two threads (e.g. the name of a specific product).

Voir la description complète du projet
Superviseur du corps professoral :

Gerald Penn

Étudiant :

Partenaire :

VerticalScope

Discipline :

Computer science

Secteur :

Information and cultural industries; Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

Goal-Conditioned Reinforcement Learning

The goal of the project is to improve upon the methodology behind goal conditioned learning. In this framework, similar to the setup in traditional reinforcement learning, an agent interacts with an environment. However, instead of training the agent to maximize return, the agent is trained to reach a given goal at the end of the trajectory. That is, given a rollout-specific goal, the agent attempts to reach it. This goal conditioned paradigm is particularly promising for applications where the objective changes in every episode, for example, controlling a robot or a drone for different tasks; or self-driving vehicles, where the destination might change between episodes. In this project, we will explore potential improvements within the goal conditioned framework, both in the discrete and continuous action space settings.

Voir la description complète du projet
Superviseur du corps professoral :

Arvind Gupta

Étudiant :

Partenaire :

Layer 6 AI

Discipline :

Computer science

Secteur :

Information and Communications Technology

Université :

University of Toronto

Programme :

Accelerate

Développement d’un béton électriquement conducteur par utilisation des résidus de bauxite brutes ou transformés

L’objectif principal de ce projet consiste à développer une formulation de béton électriquement conducteur basé sur l’utilisation des résidus de bauxite calcinés.
Les retombées de ce projet de recherche pour le Canada sont doubles puisqu’elles permettront, dans un premier temps, une valorisation de produits recyclés issus de la production d’aluminium canadienne, réduisant ainsi l’impact environnemental de ces derniers. Dans un second temps, cela représente un potentiel économique non négligeable avec le développement d’un nouveau type de béton chauffant pouvant être utilisé dans plusieurs domaines en lien direct avec les conditions climatiques exigeantes du Canada tel que la protection hivernale des tabliers des ponts ou encore des pistes aéroportuaires qui requièrent une quantité importante de produits déverglaçants nocifs pour l’environnement et les structures.

Voir la description complète du projet
Superviseur du corps professoral :

Guy Simard;Christophe Volat;Ahmed Rahem

Étudiant :

Partenaire :

Rio Tinto Alcan (Jonquière, QC)

Discipline :

Engineering

Secteur :

Manufacturing; Mining; Professional, scientific and technical services

Université :

Université du Québec à Chicoutimi

Programme :

Accelerate

Combined relational and BERT-ranking for multilingual ad hoc document retrieval

With increasing amounts of information available online on the web, it’s crucial for search engines to filter out the content they think is useful and rank that content in decreasing order of relevance to the user’s query so that the user can just focus on the top results. Traditional techniques in search ranking focused on presence of the user’s search terms in the documents being returned by the search engine. Now, modern advances in machine learning allow us to understand complex relationships between what the user really is looking for and what the documents really are about and this research will use this understanding to make better search engine rankings. This research also leverages these advances in technology to also understand the similarities between documents for return meaningful results to user search queries in multiple languages.

Voir la description complète du projet
Superviseur du corps professoral :

Gerald Penn

Étudiant :

Partenaire :

Tealbook

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

Net-shape Manufacturing of Fins for High Efficiency Heat Exchangers

Environmental pressure to reduce greenhouse gas emissions and fuel consumption has prompted
significant worldwide activity to find effective renewable/regenerative energy solutions. Solutions
where power is produced and waste heat from the exhaust is recuperated have great potential,
especially for distributed (decentralized) power generation (DPG). The latter approach reduces energy
losses that are caused by the absence of long-distance transmission lines and minimizes the risk of
widespread electrical failure. The development of high efficiency microturbines (MT) is critical to the
success of DPG and relies on efficient heat exchangers. Brayton Energy Canada has recently
developed a new proprietary design of high-efficiency heat exchangers that could allow MT to reach
higher thermal efficiency and thus quickly become a solution for DPG if parts (the fins) could be
manufacture in a cheaper way. The proposed project aims at developing a new manufacturing process
to produce the fins in a cheaper way.

Voir la description complète du projet
Superviseur du corps professoral :

Bertrand Jodoin

Étudiant :

Partenaire :

Brayton Energy Canada

Discipline :

Engineering

Secteur :

Utilities

Université :

University of Ottawa

Programme :

Accelerate

Targeting SARS-CoV-2 (COVID-19) methyltransferases (nsp10-nsp14 and nsp10-nsp16 complexes) toward developing small molecule antiviral therapeutics

COVID-19 pandemic has brought the world to standstill with more than 3 million people infected and more than 200 000 mortality so far. It has literally brought the health care systems in many countries to the breaking point, if not beyond. The economic consequences have been devastating with millions of people out of work. We are taking a novel approach by focusing on two SARS-CoV2 (COVID-19) methyltransferases that are essential for viral replication. Both enzymes (nsp14 and nsp16) are druggable. Therefore, identifying potent inhibitor of these two proteins could be used in providing new therapeutics for COVID-19. In addition, because these proteins are highly similar in other coronaviruses such as SARS (SARS-Cov) and MERS (Middle East Respiratory Syndrome), the same drugs likely could be effective in treatment of other coronavirus infections.

Voir la description complète du projet
Superviseur du corps professoral :

Masoud Vedadi

Étudiant :

Partenaire :

Structural Genomics Consortium

Discipline :

Life Sciences

Secteur :

Professional, scientific and technical services

Université :

University of Toronto

Programme :

Accelerate

Recommending Benefits Utilization to Promote a Healthy Lifestyle

Users on the League platform have access to a number of health and wellness benefits including massage, physiotherapy, personal trainers and a variety of other programs; however, not all of them fully utilize them to maximize their wellbeing. Utilizing the health and program utilization data we want to develop robust personalized predictions that will suggest to individuals, programs that they are eligible for and would benefit their health. We are hoping to further develop League’s platform into a health hub where every user will be promoted healthy behavior and wellness programs optimized for their health profile. Our recommendations will strive to make our users happier and healthier.

Voir la description complète du projet
Superviseur du corps professoral :

Scott Sanner

Étudiant :

Partenaire :

League Inc

Discipline :

Computer science

Secteur :

Finance and Insurance

Université :

University of Toronto

Programme :

Accelerate

On the design of a new electro-refining process for the recovery of magnesium from Used Beverage Can (UBC) aluminum alloys

There is actually a societal challenge here in north America regarding the end-of-life management of used beverage cans (UBCs). China is no longer accepting several of our recyclable waste streams like UBCs. UBCs are made of aluminum that contains some level of magnesium and manganese to modulate the properties of the body and the lid respectively. UBCs can potentially be seen as a great secondary feed for the production of pure magnesium used to manufacture for example critical components in the automotive industry. It is evaluated that about 40000 tons per year of magnesium could be obtained from this waste feed stream.
The ultimate objective of this work is to design an improved electro-refining process technology to recover magnesium from aluminum melt. More specifically, we want to decrease the energetic requirements by lowering the electrode inter-distances and adjust the chemistry of the electrolyte to meet modern environmental standards.

Voir la description complète du projet
Superviseur du corps professoral :

Jean-Philippe Harvey

Étudiant :

Partenaire :

Kingston Process Metallurgy

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

Polytechnique Montréal

Programme :

Accelerate

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