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

Synthesis of Pheromone Analogs for the Control of Parasitic Insect Infestation

SemiosBIO is an entrepreneurial business trying to find a chemical basis for fighting bed bug
infestation. Bed bugs (Cimex lectularius) are paraSitic insects feeding exclusively on warm-blooded
animals, including humans. Their preferred habitat includes beds and other areas used by humans to
sleep. An infestation with bed bugs can provoke a number of health problems such as skin rashes,
allergies or psychological problems. This project deals with the chemical preparation of insect
pheromone analogs which will be tested for their potential as bed bug attractants. Should they prove
efficient they will be used as a means to control paraSitic infestations by luring the insects away from
the infestated areas. SemiosBIO Technology perceives a strong market for efficient and cost-effective
tools to detect and monitor bed bug infestations and the academic group at UBC is supporting their
business goal by providing expertise in the field of chemical synthesis.

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Faculty Supervisor:

Gregory Dake

Student:

Partner:

SemiosBio Technologies Inc

Discipline:

Physics

Sector:

University:

The University of British Columbia

Program:

Accelerate

First Time Home Buyers in a Post-COVID World

The current pandemic is changing how people work, and creating a new way to think about home. From setting up a kitchen office, to being able to drop a lengthy commute, people across Canada are interacting with their living space in new ways. First time homebuyers (FTHB) have a unique opportunity to re-evaluate what is important to them when house-hunting, but the ways in which the real estate industry communicate with prospective buyers is slow to change. This project asks Millennial FTHB directly about what they look for in a first home, and how they find that information. As a boutique property tech company, Zoocasa Realty Inc. can quickly pivot their marketing to accommodate evolving consumer values. However, without the proper knowledge of shifting markets, they risk implementing ineffective strategies. This project provides invaluable insight into an under-serviced demographic, allowing Zoocasa to identify the best path forward. And it also provides valuable insight into the rapidly transforming real estate market which will have direct and immediate impacts on urban and suburban spaces.

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Faculty Supervisor:

John Shiga;Natalie Coulter

Student:

Partner:

Zoocasa Realty Inc.

Discipline:

Sociology

Sector:

Real estate and rental and leasing

University:

Toronto Metropolitan University

Program:

Accelerate

Driver motion prediction using behaviour classifications of vehicles

A significant portion of decision making, path planning and navigation algorithms for Autonomous Vehicles (AV) rely heavily on accurate estimation of the current location as well as future trajectories of the surrounding road users. There are different kinds of drivers in urban environments, and an expert human driver will identify dangerous drivers and avoid them accordingly. However, existing autonomous driving systems often treat all neighboring vehicles the same and do not take actions to avoid the dangerous drivers.
For active safety and reduced reaction times, Gatik’s AVs need to accurately predict the behaviours of surrounding agents to be able to make safe & reliable complex decisions such as merging, unprotected left turns, lane change,
etc
The goal of this research project is to develop new techniques for enabling accurate & reliable driver behaviour
prediction to ensure safer reactions in avoiding dangerous neighboring drivers, pedestrians and cyclists, and
efficient navigation around careful drivers.

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Faculty Supervisor:

Krzysztof Czarnecki

Student:

Partner:

Gatik Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program:

Accelerate

Minimiser les efforts d’annotation lors du développement d’un modèle prédictif en traitement des langues – Phase 1

Développer un modèle prédictif en traitement automatique des langues requière la création d’un corpus annoté : un texte et des annotations que l’on tentera de reproduire automatiquement. Il s’agit d’une activité à la fois complexe (les annotations sont souvent du ressort d’un expert) et coûteuse (annotations méticuleuses à produire en grande quantité). Le projet vise à développer une expertise pour minimiser les interventions (annotations) permettant d’obtenir un modèle prédictif d’une qualité donnée.

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Faculty Supervisor:

Philippe Langlais

Student:

Partner:

LexRock AI

Discipline:

Mathematics

Sector:

Administrative and support, waste management and remediation services; Information and cultural industries

University:

Université de Montréal

Program:

Accelerate

Aide au recensement de population en Afrique par application de l’apprentissage profond aux images satellites Haute Résolution (HR) et Très Haute Résolution (THR)

Le but de ce projet est de développer une méthode basée principalement sur les images satellites afin d’estimer la taille de la population et ses déplacements dans les pays où un recensement complet est difficile à réaliser pour des raisons de coût ou d’instabilité politique. L’approche sera basée sur l’application de l’apprentissage profond aux images satellites THR pour la détection des bâtiments résidentiels et leur caractérisation en fonction du nombre d’habitants, puis l’extrapolation des résultats à l’ensemble du pays à l’aide de données satellites HR. Ces dernières vont également permettre de suivre les déplacements de population. Le site d’étude sera le Soudan, pour lequel les données du recensement de 2008 sont disponibles. Le modèle d’apprentissage profond résultant de l’entrainement sur les images de 2008 sera appliqué à des images récentes (2020) afin de guider un recensement ciblé en 2020/2021 au Soudan.

View Full Project Description
Faculty Supervisor:

Yacine Bouroubi

Student:

Partner:

Apexmachina Inc

Discipline:

Sociology

Sector:

Professional, scientific and technical services

University:

Université de Sherbrooke

Program:

Accelerate

Optimization of sentence classification for insurance applications

This research is carried out on the topic of natural language processing and specifically on word representation on Question Answering tasks. The state of the art in Question Answer task is Google’s Bidirectional Encoder Representations from Transformers (BERT) language model.
Koïos Intelligence is interested in fine-tuning this model for their closed domain artificial intelligence (AI) virtual assistant, targeted at insurance and financial applications. The general objective of this research is to improve the performance of Koïos’s NLP solutions by investigating state of the art sentence embeddings and fine-tuning BERT to the domain of insurance. Specifically, the intern will attempt to improve on BERT by examining how sentences are embedded and the impact of these embeddings on accuracy and performance of the model. The uncertainty of this work lies in whether state of the art sentence embeddings can be improved on in the context of insurance natural language datasets.
The internship project will principally focus on the acceleration and optimization of software developed at Koïos, based on research of state-of-the-art sentence embeddings. The intern will validate and test alternatives for user intent classification in order to improve the system performance.

View Full Project Description
Faculty Supervisor:

Fabian Bastin

Student:

Partner:

Koïos Intelligence Inc

Discipline:

Business

Sector:

Professional, scientific and technical services; Retail trade

University:

Université de Montréal

Program:

Accelerate

Développement d’un robot autonome pour le sarclage automatique du bleuet sauvage

Avec les progrès prodigieux des dernières années en matière d’agriculture de précision, ce projet apporte une solution originale à la problématique de la détection automatique des mauvaises herbes ainsi que leur éradication dans les bleuetières de bleuets nains (sauvages). Le principal objectif de ce projet consiste à développer un système robotisé autonome capable d’effectuer la détection automatique de mauvaises herbes permettant ainsi de cibler plus précisément les zones infestées au sol et ainsi orienter en 3D les opérations phytosanitaires de sarclage. Pour ce faire les images des surfaces dans l’environnement immédiat du robot en mouvement, à analyser pour la détection et l’éradication des mauvaises herbes seront capturées en temps réel à l’aide de caméras multispectrales positionnées à l’avant du robot. Ces images géoréférencées par rapport à un système de coordonnées associès au robot, seront analysées aussi en temps réel pour en extraire les zones infestées et ce sur la base de la signature spectrale distinctive des mauvaises herbes. Les mauvaises herbes détectées seront ensuite sarclées par un système robotisé attaché au robot autonome.

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Faculty Supervisor:

François Meunier

Student:

Partner:

ÉlectroMécanique Bécancour

Discipline:

Computer science

Sector:

Manufacturing

University:

Université du Québec à Trois-Rivières

Program:

Accelerate

Quantum Resistant High Speed Blockchain Project

Secure, open, distributed computing platforms are able to provide trustable peer-to-peer transactions without the need for trusted intermediaries. However, as quantum-computers gain power and capability, the cryptographic systems they are built on are threatened. This project will provide the system described here with quantumresistant cryptographic protocols to ensure both system security and user privacy, and build a formal mathematical model to verify the safety and liveness of the system. This is essential for the company’s value proposition, as both users and investors need to be assured that these characteristics will be stable into the foreseeable future.

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Faculty Supervisor:

Ceit Butler

Student:

Partner:

CScale Corporation

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

George Brown College of Applied Arts and Technology

Program:

Accelerate

Computational Modelling of Cannabidiol Fluorination

Cannabidiol, is a non-intoxicating cannabinoid has anecdotal and preliminary evidence as a treatment for pain, anxiety, nausea and seizures. This project aims to identify the configuration of CBD when bound in the brain. We will use established computational techniques that have not been applied to CBD binding to calculate the pose that CBD adopts when bound to the type 1 cannabinoid receptor (CB1). Using the identified configuration, we will design modifications to CBD that will increase the potency of CBD and duration of benefit, without introducing side effects. We will then use computational methods to investigate the effect of the CBD modifications to CB1 receptor binding. Iteration of the design and testing steps will continue until we identify CBD modifications that result in improved CBD binding to the CB1 receptor. Developing an improved CBD derivative into a new treatment will raise the profile of CBDV.

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Faculty Supervisor:

Glenn Sammis

Student:

Partner:

Delic Labs Inc

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

Process-integrated post-processing of high-precision additive manufactured metal parts

Located in Montréal, Canada, Nanogrande is a pioneer in the high-precision metal additive manufacturing market and the premier Canadian metal 3D printer provider. To solidify their unique market position, it is key to increase their deposition process expertise and explore technologies for process performance improvement and added value proposition. The proposed project aims to support this mission by developing post-processing integration in Nanogrande’s additive manufacturing technology and characterize the deposition process. The intern will develop a semi-automatic solution to post process 3D printed micro-parts and develop a simulator of the EP process for increased process control. Since Nanogrande is based in Montréal, expanding and improving their patented additive manufacturing technology capabilities will secure their leading market position in the customized metal product manufacturing field and could lead to the creation of new jobs and future recurrent sales on consumables thereby providing a benefit to Canada overall. In addition, this project will contribute to the formation of highly qualified personnel (one graduate student).

View Full Project Description
Faculty Supervisor:

Lucas Hof

Student:

Partner:

Nanogrande Inc

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

École de technologie supérieure

Program:

Accelerate

Development of a camelid single-domain antibody-fragment targeting phosphoTDP-43 for in vivo molecular imaging applications

Neurodegenerative diseases such as Frontal lobe dementia and ALS are difficult to diagnose early, at which point, symptoms might not be clearly noticeable and disease has already caused severe brain damage. Research on new strategies for earlier diagnosis is among the most active areas and the hope is to discover an easy and accurate way to detect neurodegenerative diseases before irreversible brain damage or mental decline has occurred. Identification of imaging biomarkers will be critical for assessment of disease and improves diagnostic accuracy. TDP-43 is a known protein to be affected in 97% of all ALS cases and over 50% FTLD cases where the abnormal phosphorylation in protein aggregates is the necessary feature. This project aims to develop and validate camelid single-domain antibody-fragment targeting phosphoTDP-43 as a biomarker and apply for early diagnosis by molecular imaging. This is a promising strategy for the early diagnosis and assessment of disease progressions.

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Faculty Supervisor:

Jon Stoessl

Student:

Partner:

Primary Peptides Inc

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program:

Accelerate

Conjugation de molécules antivirales à la surface de métaux et de polymères

L’objectif du partenariat est d’adjoindre les expertises du Professeur Gae?tan Laroche dans le domaine de l’inge?nierie de surface a? celles de la firme AVMOR, qui propose des solutions de nettoyage se?curitaires pour la de?sinfection de points de contact critiques au sein d’entreprises pour lesquelles la salubrite? s’ave?re de toute premie?re importance (restaurants, e?piceries, services de traiteurs, etc.). Les expertises combine?es du laboratoire universitaire et du partenaire industriel seront mises a? profit pour de?velopper des surfaces de mate?riaux re?sistantes aux infections virales (telle la COVID-19) et bacte?riennes de manie?re permanente. Avmor formulera un produit fini utilisant les re?sultats obtenus qui pourront e?tre commercialise?s en prenant en compte la strate?gie de prix, la facilite? d’application, la classification du produit et les performances antivirales. À terme, Avmor e?valuera le proce?de? de mise a? e?chelle, les spe?cifications du produit et la stabilite? afin de de?terminer la dure?e de vie de la formulation finale.

View Full Project Description
Faculty Supervisor:

Gaétan Laroche

Student:

Partner:

Avmor

Discipline:

Engineering

Sector:

Manufacturing

University:

Université Laval

Program:

Accelerate

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