Innovative Projects Realized

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

30156 Completed Projects

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Projects by Category

L2M – An Assistive Brain-Computer Interface game controller for those with motor difficulties

GamBit enables users to control gameplay directly with their thoughts, offering a new level of accessibility and immersion. Through seamless integration with
popular video games, GamBit empowers users to experience the thrill of gaming like never before.

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Faculty Supervisor:

Jeff Larsen

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Artificial Intelligence; Biotechnology; Life Sciences (not health)

University:

Dalhousie University

Program:

Business Strategy Internship

Real-time 3D object detection and pose estimation from multiple cameras

The project aims to build a 3D object detection system by using a number of images from multiple cameras. The system will train on instances of objects to detect other instances of the same object. This means that if, for example, we want to detect a sphere, we will make the system learn how a sphere looks like by giving some example images. Now when the system encounters a new object which looks similar to the example images, the system will detect the new object to be a sphere. Similarly the system will train for detection of more complex objects. Another component of the system is pose detection which will detect the orientation of the object defected. This means if the object detected is a cylinder, the system will detect whether the cylinder is standing upright, lying horizontally or placed in some other orientation.

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Faculty Supervisor:

Sven Dickinson

Student:

Partner:

Epson Canada Ltd

Discipline:

Computer science

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

L2M – Oil spill detection using Empowered Earth Eyes (OEEE): A space-based smart solution

The OEEE is dedicated to combating oil spills in oceans and enhancing marine ecosystem health. Utilizing advanced satellite imagery analysis and AI modeling, this cutting-edge technology enables the monitoring of vast oceanic areas globally. Its capabilities extend to the early detection of oil spills and the identification of high-risk areas prone to oil spill pollution. The core of our mission is to address the pressing problem of delayed oil spill detection, which poses significant environmental and economic risks. With an automated detection system, the OEEE offers an innovative solution to enhance the detection and monitoring of oil spills in a near-real-time manner, ensuring broad accessibility and usability across various sectors.

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Faculty Supervisor:

Jeff Larsen

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Environmental Science and Technology; Artificial Intelligence; Natural Resources

University:

Dalhousie University

Program:

Business Strategy Internship

L2M- Innovative Metal Powder Solution- Transforming metal Waste into Sustainable Additive Manufacturing Materials

NexaPowder Inc. aims to revolutionize metal 3D printing by recycling scraps and waste into affordable, eco-friendly metal powders. This will slash costs by half and reduce carbon emissions by 80%, making metal 3D printing more accessible and sustainable. The Lab2Market Launch program offers NexaPowder tailored support to develop vital business skills and secure funding, helping them bring their innovative solution to market. By partnering with NexaPowder, organizations can access cost-effective, sustainable powders that enhance manufacturing while minimizing environmental impact, paving the way for a greener future in metal additive manufacturing

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Faculty Supervisor:

Jeff Larsen

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Advanced Manufacturing; Clean Technology; Sustainability & the Environment

University:

Dalhousie University

Program:

Business Strategy Internship

L2M – Remote Estimation of Ocean Sound Speed

Our technology remotely measures sound speeds in ocean depths using acoustic techniques, eliminating the need for physical sensors to be lowered into and raised from the ocean. As sound speed is a crucial parameter in most ocean acoustics systems, our remote measurement capability revolutionizes ocean acoustics and oceanography by providing real-time sound speed data. Attending the Lab2Market Launch could help us to commercialize our technology.

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Faculty Supervisor:

Jeff Larsen

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Ocean Tech; Oil and Gas; Technology

University:

Dalhousie University

Program:

Business Strategy Internship

L2M – BoviSense AI: Intelligent Solutions for Sustainable Dairy Farming

BoviSense AI revolutionizes dairy farm management by harnessing AI-driven biometric facial recognition to ensure personalized care for every cow. Leveraging unique bovine facial features, it offers precise, non-invasive monitoring of health and productivity in real time, steering traditional farming towards a sustainable, data-driven future. Our dedication to ethical AI use and broad compatibility underscores BoviSense AI’s role in leading dairy farming into an era of enhanced efficiency, animal welfare, and environmental stewardship. With BoviSense AI, we’re not merely tracking cows; we’re shaping the future of intelligent agriculture.

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Faculty Supervisor:

Jeff Larsen

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Computer science

Sector:

Agriculture and Food

University:

Dalhousie University

Program:

Business Strategy Internship

Classification des rachis cervicaux dans la population québécoise adulte nécessitant une chirurgie

Lorsque des prothèses et outils sont développés pour la chirurgie de la colonne vertébrale, leur conception exploite des simulations numériques. Cependant, les simulations de colonne qui sont utilisées ne représentent souvent qu’un individu caucasien de sexe masculin, dans la trentaine, et sans maladie. Ceci ne correspond pas aux patient·es susceptibles de recevoir une chirurgie de la colonne au Québec, et le processus de conception en est biaisé. Le but de ce projet est donc d’évaluer la variabilité des formes et des dimensions de la colonne vertébrale de la population québécoise afin de garantir l’excellence locale en conception de prothèses et en soins de santé. Pour cela, une analyse de classification sur les images médicales que des patient·es d’un hôpital du
Québec ont volontairement cédées à la recherche sera réalisée afin d’en ressortir ce que serait, par exemple, une colonne de taille M par rapport à une colonne de taille L.

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Faculty Supervisor:

Yvan Petit;Jean-Marc Mac-Thiong

Student:

Partner:

Numalogics

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

École de technologie supérieure

Program:

Accelerate

L2M – Imprinted polymeric microstructures for specific capturing of target analytes

For those who need precise and selective capturing, releasing, and sensing of substances within complex samples and harsh conditions, SensoFluidix offers microparticles and membranes with monodispersed shapes and sizes, serving as tailor-made synthetic recognition elements within disposables microfluidic cartridges and sensors. Unlike natural receptors, our cost-effective synthetic receptors can endure harsh environments, boast a prolonged shelf life, and are user-friendly, easily stored, and animal-free. Our technology can be engineered for a wide range of target analytes, including ions, and whole microbial cells. We aim to address a series of validated problems for well-identified customers in environmental monitoring, mining, battery recycling, and analytical chemistry industries.
The Mitacs BSI program will enable us to grasp the fundamentals of lean startup methodology and take significant strides toward commercializing our ideas. This includes finalizing our business model under the guidance and support of mentors, facilitators, and supervisors, providing us with invaluable expertise and direction.

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Faculty Supervisor:

Jeff Larsen

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Water; Environmental Science and Technology; Health and Related Sciences & Technology

University:

Dalhousie University

Program:

Business Strategy Internship

L2M- Launching BravoZulu Create

Transition and reintegration from service represents a profound psychosociocultural change for individuals who release from military service (i.e. Veteran). Service is impactful to health and wellbeing over the life course. Veterans represent a special population in Canada with heterogenized needs. Acculturation and loss of service identity presents the need for social reintegration and to restore identity through alternative roles (Thompson et al., 2017). There is a need to develop programs and services that reflect the heterogenous needs of Veterans. Community, belonging, autonomy, ability, purpose, and meaning of art and craft suit a myriad of transition and reintegration demands however access and resources to art and craft could represent barriers to participation. There is currently no online community that supports Veteran art/craft endeavours domestically nor internationally. Such a novel technology represents a valuable contribution to Veteran health by supplying a neutral space for Veterans to convene, share art/craft and learn as they choose as well as to co-create in a meaningful way.

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Faculty Supervisor:

Jeff Larsen

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Sociology

Sector:

Health and Related Sciences & Technology; Social Innovation; Other

University:

Dalhousie University

Program:

Business Strategy Internship

Identification de stratégies d’approvisionnement en naissain de moule aux Îles-de-la-Madeleine

Aux Îles-de-la-Madeleine (Qc), les mytiliculteurs s’approvisionnent en jeunes moules (naissain) dans une lagune côtière, le Bassin du Havre-Aubert (BHA), car les stocks récoltés (captage) présentent une résistance particulière au stress, en lien avec une diversité génétique plus importante. Toutefois, face au manque d’espace disponible au BHA et à une variabilité interannuelle du succès de captage, cette industrie aquacole considère comme prioritaire l’évaluation du potentiel d’approvisionnement en naissain de moules performant et ce, à l’échelle de l’archipel. Dans ce contexte, l’objectif de ce projet est d’identifier les stratégies alternatives d’approvisionnement qui reposeraient principalement sur l’exploitation d’autres plans d’eau. Élaborés avec la volonté de limiter la colonisation d’espèces nuisibles au captage, plusieurs scénarios de culture seront testés sur la base d’une évaluation de la performance du naissain (croissance, survie, génétique). Les retombées directes du projet seront l’obtention d’une quantité suffisante de naissain de moule de qualité à l’échelle de l’archipel, permettant ainsi aux entreprises mytilicoles d’atteindre leurs objectifs de production et de rentabilité.

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Faculty Supervisor:

Réjean Tremblay

Student:

Partner:

Merinov (Rimouski, QC);Les moules de culture des Îles inc;Grande-Entrée Aquaculture inc;La Moule du large inc;Cultimer Inc

Discipline:

Life Sciences

Sector:

Aquaculture and Fishing; Natural Resources; Agriculture and Food

University:

Université du Québec à Rimouski

Program:

Accelerate

Modélisation spatio-temporelle de pertes dues aux tempêtes de grêle au Canada

Ce projet a pour but d’établir un modèle considérant la dépendance dans l’espace et dans le temps, entre les tempêtes de grêle causant des dommages assurables. Nous utilisons un modèle hiérarchique Bayesien, où la fréquence des pertes assurables sera scindée en partie que nous définirons comme faisant partie du noyau et des extrêmes. Nous utilisons la méthode Monte Carlo Hamiltonienne pour l’estimation des paramètres. Cette modélisation pourra ensuite être utilisée afin de combiner des taux de dommages par rapport à la valeur des effets assurés. L’objectif est de fournir un modèle libre d’accès, qui représente l’évolution des tempêtes de grêle.

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Faculty Supervisor:

Klaus Herrmann;Melina Mailhot

Student:

Partner:

Desjardins Assurances Générales

Discipline:

Mathematics

Sector:

Finance and Insurance

University:

Université de Sherbrooke

Program:

Accelerate

Deep Reinforcement Learning in Optimal Market-Making

On June 1, 2021, Futures First Canada and FinML began a pilot collaborative project involving three Canadian universities by-way-of a MITACS Accelerate internship (IT25712) which jumpstarted an initiative to use cutting edge techniques in machine learning, financial mathematics, and AI for making predictions in financial markets. This goal is integral to the business operations of Futures First and is currently a popular topic in academic research. The pilot project created a basis for this current project application which will continue the effort, extending positive academic results and furthering integration into the company’s infrastructure. This next project will extend previous research from project IT35694 which focused on applying SOC (stochastic optimal control) to algorithmic and HFT (High-Frequency Trading) problems. The trading problem Futures First specifically focuses on is market-making, which is one of the most heavily studied trading problems in the futures trading environment. The main subject of this new project will be to utilize the novel topic of deep reinforcement learning to generate optimal market-making solutions. This will be a challenging project where we uncover the obstacles for applying the academic theory around deep reinforcement learning in practice.

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Faculty Supervisor:

Anatoliy Swishchuk

Student:

Partner:

Futures First Canada Inc

Discipline:

Mathematics

Sector:

Finance and Insurance

University:

University of Calgary

Program:

Accelerate

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