Projets novateurs réalisés

Cartographie et classification du terrain à potentiel avalancheux au Nunavik (nord du Québec)

Les aléas naturels et les risques associés deviennent plus fréquents dans les régions arctiques et subarctiques du Canada, incluant le Nunavik. Ils peuvent avoir des impacts dévastateurs sur la sécurité, le bien-être, l’économie de subsistance, les activités et l’identité culturelle des communautés inuites. La nature et l’ampleur des événements varient selon les paramètres environnementaux et le degré d’exposition des sites. Il est donc primordial de mener des recherches collaboratives sur les aléas naturels, notamment les avalanches de neige, dont les connaissances sont fragmentaires. Actuellement, les cartes utilisées par les entrepreneurs et aménagistes sont basées sur des informations anciennes (30 ans) et non sur des études de terrain solides ni sur des échanges avec les communautés concernées. Avec les changements humains (hausse démographique) et naturels actuels, il est essentiel de refaire ces cartes en utilisant des approches méthodologiques nouvelles. Cette étude vise à identifier les facteurs déclencheurs d’avalanches pour déterminer les villages les plus à risque. Ces facteurs incluent la topographie, la géologie de surface, la végétation et les conditions météorologiques. L’objectif est de fournir à l’Administration régionale Kativik des connaissances et des simulations pour orienter l’aménagement du territoire du Nunavik.

Deep Learning-Enabled 3D Fluorescence Imaging for Cancer Surgery

The Princess Margaret Cancer Centre, part of the University Health Network (UHN), is Canada’s largest cancer hospital and one of the top 5 cancer research centres in the world. This internship will take place in the Guided Therapeutics (GTx) lab, part of the cancer centre’s research institutes. The GTx lab is developing novel devices, algorithms, and nanoparticles to guide cancer surgery. The multi-disciplinary team consists of surgeons working alongside engineers, physicists, computer scientists, and chemists. Novel technology developed in the lab translates to first-in-human clinical studies, with a strong academic focus (e.g., peer-reviewed papers, conference presentations). Cancer surgeons face the challenge of determining how deep a tumour invades below the surface. Inaccurate resections leave tumour behind and negatively affect patient outcomes. Medical devices to image the patient during surgery may help guide more precise tumour removal. To this end, the GTx lab is developing an AI-powered optical imaging system to measure tumour depth. To date, this prototype system has undergone pre-clinical testing in simplified, 3D-printed models derived from real patient cases. This internship will help the team optimize this technology to work in more realistic preclinical experiments, in preparation for future clinical studies with cancer patients.

Biocarbon from agricultural waste for energy storage

The proposed research focuses on the development of biocarbon materials from waste spent clay and soapstocks from vegetable oil processing. The biocarbon will be used as the filler in developing rubber composite material as a potential substitution for carbon black produced from petroleum sources. The intern will work with the team of graduate students and postdoc fellow and industry partners and gain skills in green material synthesis methods and characterization techniques.

The effect of dynamic information display on perception of public restroom cleanliness

The cleanliness of restroom drives people’s preferences. In places such as hotels, restaurants and hospitals, a dirty bathroom will drive away potential customers as it lead them to question the cleanliness of the whole facility. Visionstate Inc. developed WANDA (Washroom Attendant Notification Digital Aid), a LCD touch screen that display the time of most recent restroom service and a interactive interface to request restroom maintenance. The proposed study is to investigate whether features of WANDA enhance people’s perception of bathroom cleanliness. The study asks people to fill out an anonymous survey when they exit a public restroom, asking about how clean they feel the bathroom is. If the study found people perceive the bathroom to be cleaner with presence of WANDA, the finding would help Visionstate Inc. to promote WANDA to clients. If WANDA is ineffective to influence the perception of cleanliness, the finding might help Visionstate to further improve product features.

Impact Assessment of Predictive Capabilities

Comprehensive Healthcare at Home (CHAH Technology) is a Toronto-based health-tech startup leveraging AI to enhance home-based healthcare. The company develops predictive models that monitor patient health, detect early warning signs, and facilitate timely interventions to prevent hospitalizations.
The healthcare system in Canada faces growing challenges due to an aging population and high public healthcare costs. CHAH’s technology addresses these issues by providing proactive and cost-effective care in home environments. This internship will assess the real-world impact of CHAH’s predictive models in collaboration with St. Joseph’s Healthcare in Hamilton, a leading research institution.
By evaluating key performance indicators (KPIs) such as hospital readmission rates, cost savings, and patient satisfaction, this project will validate CHAH’s approach and support its integration into broader healthcare frameworks. The insights gained will enhance CHAH’s predictive models, improve adoption rates among healthcare providers, and contribute to sustainable healthcare solutions.

Étude des potentialités du Biochar pour des nouveaux matériaux biosourcés bas carbone

La demande croissante de matériaux écologiques et abondants a fait du biochar un agent de renfort très recherché dans les applications automobiles. Le biochar possède des propriétés uniques, telles qu’une structure poreuse, une grande surface spécifique, une haute stabilité thermique, une bonne conductivité, une source de matière première renouvelable et abondante, ainsi qu’une durabilité environnementale. Ces caractéristiques contribuent à la performance exceptionnelle, aux avantages environnementaux et aux faibles coûts de production des composites à base de biochar. Ce projet vise à explorer l’impact des méthodes de préparation et des paramètres de processus, tels que le type de matrice, les pourcentages de fibres et les additifs, sur la formulation et les propriétés des biocomposites à base de biochar. Il offre une analyse approfondie de la manière dont les modifications des propriétés chimiques du biochar améliorent les caractéristiques des matériaux biosourcés et renforcent l’interface entre le biochar et la matrice dans les biocomposites. De plus, le projet met également en lumière le potentiel de corréler les propriétés chimiques avec les propriétés diélectriques du biochar en utilisant des outils d’apprentissage automatique.

Anisotropie de l’aluminium suivant les chemins de déformation et taux de recristallisation

Afin de contrôler les propriétés mécaniques des pièces en aluminium, il est nécessaire de mieux comprendre l’effet de la déformation et de la recristallisation dans le processus de fabrication. Le présent projet documentera l’anisotropie de l’aluminium suivant différents chemins de déformation et taux de recristallisation. Le stagiaire pourra ainsi être initié à différentes techniques de caractérisation et contribuera à alimenter une base de données.

Rare Disease Detection

This project aims to improve a tool that helps doctors detect rare diseases by making it easier to find important information in patient records. The intern will work on creating a system that uses advanced computer models to organize and retrieve data from electronic medical records (EMR). By doing this, the tool will become more efficient at identifying signs of rare diseases. The intern will be guided by a team of experienced researchers, ensuring high-quality work and valuable learning. The expected benefit to the partner organization is a more powerful and accurate tool for detecting rare diseases, which can lead to better patient care and outcomes.

Addressing Basis Risk in Agricultural Index-Based Insurance

The objective of the proposed research is to design and implement an innovative IBI scheme capable of minimizing basis risk. Forage insurance will be used as an example to empirically examine the effective implementation of the IBI, through establishing an adequate relationship between the weather index and forage yield. Therefore, a second objective of the proposed research is to help increase producer demand for forage insurance. Using long term data on forage yield and insurance coverage, panel data econometrics and statistical methods will be used to assess the relationship between the index and the loss exposure. The research will consider alternative contract structures, such as multiple variable indices that are capable of incorporating extended dry periods during the critical growth phase, in addition to excess rainfall, for example. Further, other contract structure considerations will include analysis on spatial basis risk and the corresponding allocation of coverage to multiple rainfall stations. The feasibility of selective forage insurance schemes will be tested, through field experiments, group discussions and key informant interviews. This problem is of significant importance to the partner organization, Guy Carpenter & Company, as well as to producers, provincial crop insurance companies, federal and provincial governments, and reinsurers.

ESROP – Osaka University – Developing a Robot Manipulator to Cut Plant Leaves for Agricultural Research

This project focuses on developing a robotic arm manipulator capable of accurately cutting plant leaves for genetic analysis, improving the efficiency and precision of agricultural plant research. In current studies, researchers must manually cut leaves from hundreds of plants, a time-consuming process that introduces inconsistencies due to varying plant conditions over time. Automating this task will allow for faster, more reliable, and standardized sample collection, reducing human error and ensuring that all plants are processed under the same conditions.

To achieve this, the project will utilize an RGB-vision based system to help the robot accurately identify and target plant stems, which are too thin to be reliably detected by standard depth sensors. The robotic manipulator will need to operate with high accuracy, ensuring precise cuts without damaging the plant or disrupting the overall workflow.

By advancing robotic automation in life science research, this project will contribute to more efficient agricultural studies, particularly in understanding plant responses to drought. The work will also help improve laboratory automation by developing new methods for robotic control and motion planning. This collaboration will provide valuable insights into automation for plant science and precision agriculture, benefiting research efforts in both robotics and biology.

Bio-Vault 3: Design and prototyping of a full-scale low-embodied carbon structure using biochar-based composites

Building materials made from bio-based feedstock such as biochar requires less embodied energy and has carbon sequestration capacity. Their use in construction reduces the overall Global Warming Potential (GWP) of building materials, facilitates environmental repair, and reduces climate impacts from environmentally intensive industry sectors such as agriculture and aquaculture. Bio-based composites are typically low in strength. As a corrective, a method was investigated in a previous work to develop structural strength through intelligent planning, execution and material characterization by designing and physically prototyping a small-scale geometrically optimized structure using biochar-based composites. The work demonstrated a prove of concept that biochar-based composites can be used for structural applications. This proposed study will refine the means and method and apply them to a full-scale construction.

The general objective is to design and physically prototype a full-scale low-embodied carbon structure using biochar-based composites. The proposed methodology will analyze structural forces and GWP in a structural and low-carbon optimization design framework according to the sub-objectives: 1) Construction means and methods refinement, 2) Full-scale fabrication and installation.

L2M – Creditcliq

Creditcliq is a fintech solution designed to help newcomers to the U.S. and Canada access financial products like credit cards, loans, and rentals by sharing their home country credit history with local banks and credit unions.