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

Smooth Guide Hair Interpolation for Procedural Grooming

Most recent animated films such as Peter Rabbit 2 or DC League of Super-Pets come to life with many hairy and furry characters. In this project we will build on recent advances in computer graphics to develop better tools for grooming hair and fur. We aim to improve the experience of artists in the animation and visual effects industries by reducing the time spent manually grooming hair and by providing tools to deal with complicated geometries such as the corner of a character’s mouth. Animal Logic will benefit from freeing up artists’ time and energy to focus more on storytelling and less on meticulously grooming each character.

Voir la description complète du projet
Superviseur du corps professoral :

Alla Sheffer

Étudiant :

Partenaire :

Animal Logic Studios (Vancouver) Ltd.

Discipline :

Computer science

Secteur :

Information and cultural industries

Université :

The University of British Columbia

Programme :

Accelerate

AlleyCorp Nord : MLOps pour les incubateurs

AlleyCorp Nord (ACN) a créé et développé plus de 20 entreprises sur un modèle d’incubation propriétaire (dont la plus connue MongoDB). Les entreprises fondées par AlleyCorp ont levé collectivement plus d’un milliard de dollars en capital-risque et emploient des milliers de personnes à travers l’Amérique du nord. Beaucoup de ces entreprises visent à utiliser l’apprentissage automatique (ML) à des fins d’innovation et de leviers de croissance. Cependant, malgré l’augmentation des outils de ML pour tenter de rendre l’expérimentation plus rapide et plus rationnelle, il n’est toujours pas très simple pour les chercheurs en ML ou les personnes non-ML ayant une expérience technique ou du domaine de valider de nouvelles idées sans investir beaucoup de temps et d’argent. L’objectif du stage est d’apporter une contribution en génie logiciel pour la simplification du processus ML.

Voir la description complète du projet
Superviseur du corps professoral :

Christian Gagné;Mohamed Aymen Saied

Étudiant :

Partenaire :

AlleyCorp Nord

Discipline :

Computer science

Secteur :

Professional, scientific and technical services

Université :

Université Laval

Programme :

Accelerate

3D printing of high-performance composites for advanced aerial drones

Advanced aerial drones have extensive applications in industry, e.g., water resources management, warehouse operations, search & rescue, and geographic mapping. Current drone body frames mainly use low-temperature polymers with limited thermal and structural performance. In this project, high-temperature high-performance polymers and continuous carbon fiber composites will be used for 3D printing drone body frames. It can improve tensile strength and modulus by 16 and 34 folds, respectively, compared with standard polymers. It is a collaboration with SOTI Aerospace, which is focused on self-navigating aerial drones. The objective is to design, analyze, 3D print, and test drone body frames that meet or exceed SOTI requirements while minimizing weight. 3D printing allows for the fabrication of complex geometries with minimal materials waste. This way, SOTI can significantly improve its current drone models while reducing weight, materials waste, and cost.

Voir la description complète du projet
Superviseur du corps professoral :

Kazem Fayazbakhsh

Étudiant :

Partenaire :

SOTI Inc

Discipline :

Engineering

Secteur :

Information and cultural industries; Professional, scientific and technical services

Université :

Toronto Metropolitan University

Programme :

Accelerate

Investigating Sugar Kelp’s potential as an environment-friendly biofertilizer for sustainable potato production

The proposed research aims to evaluate different processing techniques to ensure sugar kelp’s safety and stability as a biofertilizer for potato production. And nutrient contents of the processed kelp will be determined, and plot-scale experiments will be conducted to grow potatoes under exclusive and in-combination application of processed sugar kelp with synthetic fertilizers for 2-years. Impacts of the treatments on the soil health and GHG emissions will also be determined. All that will help determine effectiveness of sugar kelp as a biofertilizer for sustainable potato production. The Food Island Partnership is committed to supporting sustainable agriculture in PEI as per its mission. Their guidance and support during the project will help the partners in properly conducting the experiments. And its accelerated dissemination and widescale adoption causing safe transitioning to more sustainable agriculture and socioeconomic development, as per its mission.

Voir la description complète du projet
Superviseur du corps professoral :

Gurpreet S. Selopal;Aitazaz Farooque;Aitazaz Farooque;Gurpreet S. Selopal

Étudiant :

Partenaire :

Food Island Partnership

Discipline :

Engineering

Secteur :

Agriculture

Université :

Dalhousie University; University of Prince Edward Island

Programme :

Accelerate

Developing a Guidance List for repOrting Bibliom AnaLyses (GLOBAL)

A bibliometric analysis is a way to measure and analyze the impact and productivity of a person, organization, or field of study using the number and types of publications, citations, and other metrics. It can be used to identify patterns and trends in research, evaluate the performance of individual researchers or research groups, and identify areas of growth or decline in a field. The Guidance List for the repOrting of Bibliometric AnaLyses (GLOBAL) is a set of guidelines that will help researchers and authors report their bibliometric analyses in a consistent and transparent way. Over recent years, a large increase in the number of bibliometric analyses have been published, but little guidance is available on how to report it properly. This lack of guidelines is a problem, because it makes it difficult for others to understand, interpret, and critically assess the quality of the research. To address this issue, the intern and team propose to develop a set of guidelines through a process that involves reviewing existing literature and consulting with experts, then testing and refining the guidelines through surveys and a pilot study.

Voir la description complète du projet
Superviseur du corps professoral :

David Moher;Stefanie Haustein

Étudiant :

Partenaire :

EBSCO Health

Discipline :

Mathematics

Secteur :

Information and cultural industries; Retail trade

Université :

University of Ottawa

Programme :

Elevate

Enhanced & Editable Deep Fakes

Traditional Computer Generated Imagery (CGI) splits the process into separate stages: we model geometry; apply textures and define surface properties; animate motion; and apply lighting; before combining the elements when rendering imagery. Deep-learning methods such as Deep Fakes, or NeRF train a network to combine many of these steps into a single network, and are able to produce convincing results in this way. By combining these different aspects of image generation into a single unit, these networks also make it challenging for an artist to edit the properties of the network in an intuitive way. This is because the underlying representation, which is typically a latent vector, doesn’t have a simple connection with the high-level controls an artist expects. We wish to explore ways of giving our artists intuitive ways to control neural rendering. We also want to explore ways of enhancing our results by adding additional inputs to the process.

Voir la description complète du projet
Superviseur du corps professoral :

David Lindell

Étudiant :

Partenaire :

DNEG

Discipline :

Computer science

Secteur :

Information and cultural industries

Université :

University of Toronto

Programme :

Accelerate

AI-driven Predictive Models and Consumer Insight for Trade Optimization Improvement

The proposed project is to develop AI strategies to provide precision marketing through consumer segmentation and recommender systems, as well as to promote events that shall meet various business goals for retailers and Unilever. Successful outcomes will feed into an On-Demand AI Engine aimed at improving consumer engagement and pricing strategy in the consumer packaged goods sector.

Voir la description complète du projet
Superviseur du corps professoral :

Scott Sanner;Chi-Guhn Lee

Étudiant :

Partenaire :

Unilever Canada Inc

Discipline :

Computer science

Secteur :

Manufacturing; Wholesale trade

Université :

University of Toronto

Programme :

Accelerate

Prototype development for a system to generate on-road wind conditions within automotive wind tunnels

Wind tunnels are an important tool that are used for automotive performance testing. The focus of the research project is on the development of a system to be used in wind tunnels that can simulate gusts and sweeps that vehicles often experience while on the road. This is important since it can enhance vehicle testing capabilities for new vehicle designs with improved performance such as greater fuel or energy efficiency. The intern will research methods to cause gusts and sweeps events using aerodynamic surfaces and mechanical systems. Ultimately the goal is to design a build a prototype system and demonstrate gusts and sweep generation through measurement and analysis of effected air flows in the wind tunnel.

Voir la description complète du projet
Superviseur du corps professoral :

Ronald Hanson

Étudiant :

Partenaire :

Aiolos Engineering Corporation

Discipline :

Engineering

Secteur :

Professional, scientific and technical services

Université :

York University

Programme :

Accelerate

Towards AI Assisted Training Tool: Automated Identification of Calcifications in Optical Coherence Tomography Breast Tissue Images.

Breast cancer is the most common cancer (excluding non-melanoma skin cancer) in 109 countries including Canada. Approximately 70% of the breast cancer surgeries are breast-conserving lumpectomy procedures. Histopathology analysis typically require 2-4 days, resulting in the need for a second surgery if a margin is positive. Perimeter Medical is developing advanced Optical Coherence Tomography (OCT) imaging tools to visualize margins at the time of surgery. One of the keys needs is the training of medical professionals who would interpret images during surgery. Intern will contribute to development of an AI based solution that will have a click to reveal functionality to identify different features in OCT images. Intern will develop a binary classifier to identify calcifications which might be an early sign of cancer. Intern will learn various aspects of AI development from data labeling, curation to model building and optimization while Perimeter Medical accelerates the development of training tool.

Voir la description complète du projet
Superviseur du corps professoral :

Timothy Chan

Étudiant :

Partenaire :

Perimeter

Discipline :

Computer science

Secteur :

Artificial Intelligence; Health and Related Sciences & Technology; Biotechnology

Université :

University of Toronto

Programme :

Accelerate

Implementing Strategies for Community Engagement and Development

The work by the interns will help Oak Table to revamp and improve services delivered through several programs, improve communication, improve outreach, assist with the food preparation and assist with recovering from Covid-19 pandemic. These projects will assist Oak Table in recruiting additional volunteers and strengthening organizational capacity, specifically in regards to recreational, educational, and cultural programming needs as they move forward from the pandemic. These projects center around community building and engagement, and will help Oak Table to better fulfill its mission of providing support, hospitality, and advocacy in a safe and respectful community. This project will also run for 5 years. Each subsequent intern in 2024 and on will continue to build on the existing work to date and continue to support Oak Table by aiding in service delivery, improving service delivery and helping Oak Table continue to recover from Covid-19 and the significant volunteer loss.

Voir la description complète du projet
Superviseur du corps professoral :

Shauna MacKinnon

Étudiant :

Partenaire :

Oak Table

Discipline :

Sociology

Secteur :

Health and Related Sciences & Technology

Université :

University of Winnipeg

Programme :

Business Strategy Internship

Student Support for New Content for RaY Programs

Resource Assistance for Youth, RaY, is a street level non-profit organization that works with youth, ages 0-29, providing integrated programs and services. Their Hub Model is designed to provide everything street and marginalized youth need on their terms. This includes health supports, housing supports, mental health and addiction supports, basic needs, drop-in services, street outreach, employment and training, and cultural supports. Based on their personal experience and connections with youth, RaY has developed new and innovative programming such as an employment and training program that responds to the emerging needs of youth.
The Level Up! Education and Training program, provides education and training to youth between between 18-29, targeting youth that have a connection to Employment an Income Assistance (EIA) and/or CFS. The level up program has two streams. First, the Level Up! Launch Pad, a 9 week paid training program offered in an alternative classroom environment which focuses on building life skills. Second, the Level Up! Lift Up, a 7 week paid training program in a classroom atmosphere where you will gain skills for the desired job and how to keep the job.

Voir la description complète du projet
Superviseur du corps professoral :

Shauna MacKinnon

Étudiant :

Partenaire :

Resource Assistance for Youth

Discipline :

Sociology

Secteur :

Health and Related Sciences & Technology

Université :

University of Winnipeg

Programme :

Business Strategy Internship

New Directions – Training and Mentoring Improvements

The T.E.P Program within the organization of New Directions works with young woman, individuals involved within the criminal justice system and those who have been diagnosed with pre-natal exposure (FAS, FASD & ARND) between the ages of 12-17 who happen to be indigenous. Their goal is to offer empowerment of the individuals that they work with, through the means of introducing the girls within the program to their indigenous culture/ways, developing tools that allow them to engage in social environments and educate them on matters such as emotional well-being, sexuality and reproductive health issues. This, which happens to be all done as the mentor and participants develop an interpersonal relationship to understand one another in the different scenarios they find themselves in, that challenges these ordeals.

Voir la description complète du projet
Superviseur du corps professoral :

Shauna MacKinnon

Étudiant :

Partenaire :

New Directions

Discipline :

Sociology

Secteur :

Education; Health and Related Sciences & Technology

Université :

University of Winnipeg

Programme :

Business Strategy Internship

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