Projets novateurs réalisés

AI Chatbot for HGS Website

The AI-driven chatbot role is designed to efficiently respond to a variety of queries related to HGS, including its capabilities, products, offerings, sales support, and case studies. Additionally, the role involves providing detailed information about the company, such as job openings, application processes, and general inquiries. A key objective is to assist in generating leads and promoting open positions, thereby supporting the company’s growth and recruitment efforts. This role is crucial in ensuring that users receive accurate and timely information, enhancing their overall experience with HGS.

Demtroys: Détection d’anomalies énergétiques. Notifications intelligentes

Demtroys est une entreprise operant dans le domaine de l’lnternet des Objets (loT) avec une specialisation dans les systemes de chauffage. L’equipe, composee de professionnels dedies, travaille sur l’elaboration de solutions pour optimiser l’efficacite energetique de batiments residentiels et commerciaux.

L’objectif de ce projet est de minimiser le gaspillage energetique. En identifiant les evenements de perte d’energie, Demtroys vise a permettre a ses clients d’informer leurs locataires commerciaux sur les pratiques d’efficacite energetique. Cela contribue a l’adoption d’un mode de vie plus durable et respectueux de l’environnement. Demtroys vise a etre un acteur significatif dans la transition energetique grace a ses solutions loT pour le chauffage.

Enabling Customization of OS Memory Eviction Policies

The project aims to optimize memory management in operating systems by allowing user-space applications to design custom memory eviction policies. Traditional memory management policies, embedded in operating systems, often perform well on average but fail to deliver optimal performance for specific applications. This research will explore the use of eBPF technology to create more tailored memory management solutions with a particular focus on eviction policies, improving performance and reducing memory usage in data centers, where memory costs represent a significant financial burden.

LastMile AI Project

Our research aims to address the trustworthniess, scalability and interpretability of LLMs in the RAG enviroment by generating not only novel academic insights but also practical technology that helps enterprise AI users better understand, evaluate, and debug. By achieving a deeper, theoretically and empirically grounded understanding of how LLMs behave within RAG systems, we seek to provide actionable insights directly to users of industrial systems. Current technical approaches to evaluating LLM responses are often limited to coarse-grained classifications, which can be inaccurate, difficult to interpret, and not easily actionable. Our goal is to develop technology that provides users with fine-grained, interpretable, and actionable information, allowing for meaningful improvements to production systems that would otherwise be difficult to achieve.

Non-invasively guided ultrasound hyperthermia mediated treatment of cancers in vivo using drug-loaded temperature sensitive liposomes

Chemotherapy uses drugs to treat cancer, but often causes significant side effects as the drug can spread throughout the body and affect healthy tissues as well. These side effects can be reduced by capturing drugs into nanoparticles such as liposomes that can enter tumors directly, but are too large to accumulate in healthy tissues. However, releasing the drugs from these liposomes is still a challenge. Heat treatments are often used in combination with these liposome nanoparticles to release drugs from liposomes directly in the area of heat treatments. As an added challenge, the risk of overheating can also damage surrounding healthy tissues. This project aims to develop an integrated ultrasound system that takes temperature images using an ultrasound imaging device to control heat treatments in real-time using a second ultrasound treatment device. The integrated system will be used to treat tumors grown on mouse models by releasing drugs contained in liposomes. This is expected to yield publications and a new IP for Cancer Rx, as well as a new feature for ultrasound systems developed by FUJIFILM VisualSonics Inc.

Improvement in 3D printability and functional properties of plant and algal proteins by cold plasma technology

The three-dimensional food printing (3DFP) offers the food industry and consumers customizable food preparation and manufacturing possibilities. Several food products including plant proteins have been utilized in 3DFP applications. However, the printability of plant proteins needs to be enhanced to develop novel food structures with improved stability. Our previous research showed that atmospheric cold plasma (ACP) as a novel pre-treatment technology can be used to improve the 3D printability and stability of plant protein structures. However, more research is needed to expand the application of ACP pre-treatment to improve the printability of a wide range of plant proteins.

This research project aims to advance our understanding of the application of ACP technology to improve the 3D printability and functionalities of plant and algal proteins. In this international collaborative project, we plan to utilize the crops and resources in Canada and Chile. The outcomes of this project can introduce new tools and opportunities for Canada’s and Chile’s food sectors, enhancing their ability to produce and export value-added products. In the long term, we aim to establish the 3DFP Network, a new initiative designed to foster collaboration between industry and academic partners, creating a global hub for 3DFP research.

Application of Artificial Intelligence (AI) for improved and sustainable swine production

Artificial Intelligence (AI) and data-driven decision making are booming in all sectors, and pig production makes no exception. In this fast-evolving landscape there is a need to assess which areas would benefit the most from AI and have an impact on productivity and sustainability of the Canadian swine industry. There is also a need to objectively evaluate new tools available in controlled environments, and assess whether they are practical, accurate, affordable and sustainable in commercial settings, with a focus on the use of real-time data in a production context. In a project led by the Canadian Centre for Swine Improvement, in collaboration with Prairie Swine Centre, the intern will work on collecting, annotating and analyzing data collected in pig barns, as well as developing and testing new algorithms to automatically predict pig health status and welfare.

Eddyfi : Intelligence artificielle appliquée au test non destructif de surface de pipeline

En Amérique du Nord, plus de 4 millions de kilomètres de pipelines transportent pétrole et gaz, avec la corrosion
sous contrainte comme principal défi de maintenance. Les opérateurs de pipelines effectuent des inspections
régulières pour garantir la sécurité publique, impliquant des coûts importants. Eddyfi Technologies a développé
des technologies avancées d’inspection non destructive qui offrent une détection et un dimensionnement des
fissures rapides et précis. Le projet vise à intégrer l’intelligence artificielle pour optimiser l’analyse des données
obtenues par ces technologies, réduisant ainsi le temps et les coûts d’analyse. Un stagiaire participera à ce projet
en développant un modèle de segmentation des données issues des inspections. Une innovation clé de ce
modèle sera l’estimation de la fiabilité des prédictions, permettant ainsi aux opérateurs de prendre des décisions
informées rapidement et de minimiser les risques d’incidents. Cette estimation de confiance est essentielle pour
assurer une maintenance efficace et sécurisée des pipelines.

La divulgation efficace des facteurs ESG : une approche au regard du droit suisse et du droit canadien

Ce projet de recherche qui s’inscrit dans le cadre d’un mémoire de Master co-dirigé entre l’Université de Lausanne et l’Université de Montréal, propose une étude comparative des mécanismes de reporting extra-financier dans les systèmes juridiques suisse et canadien. Il explore le rôle du droit dans la divulgation efficace des facteurs environnementaux, sociaux et de gouvernance (ESG).
La première partie analysera comment le droit peut soutenir un reporting extra-financier clair, systématique et contraignant, tout en clarifiant les obligations des entreprises et en harmonisant les norme. Il sera aussi question du cadre législatif le plus approprié.
La deuxième partie portera sur les devoirs de diligence et de transparence liés aux minerais et métaux provenant de zones de conflits et au travail des enfants, comparant les normes suisses et canadiennes.
Ce projet propose de fournir des solutions concrètes aux défis actuels de la RSE, en considérant non seulement le contexte canadien et suisse, mais aussi l’évolution des normes internationales. Dès lors, il s’agira de déterminer comment ces deux juridictions peuvent s’inspirer l’une de l’autre pour améliorer leurs cadres législatifs respectifs en matière de RSE.

Transition Écologique des Trains Passagers au Québec : Étude et Modélisation de Trains à Batterie dans des Conditions Climatiques et Opérationnelles Variées

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Ce projet de recherche vise à accélérer la transition écologique des trains passagers en étudiant la conversion des trains diesel en trains à batterie dans le contexte du Québec, où les températures varient de -20 à 40 °C, la charge mécanique fluctue aux heures de pointe et le relief varie selon les itinéraires. L’accent sera mis sur les implications énergétiques et la charge sur le réseau électrique due à l’utilisation de trains à batterie. La modélisation sous Matlab permettra d’analyser l’impact des variations de puissance lors de différentes phases d’opération (accélération, décélération, maintien de vitesse, arrêt et recharge). Le projet vise à outiller EXO et la communauté scientifique pour évaluer la faisabilité du remplacement des locomotives diesel par des locomotives à batteries.

Cross Functional Team Efficiency in Growing Organizations

SmartSimple is experiencing tremendous growth and need to ensure our business operations can keep up with the demands on the organization. Given our multi-location operations and the collaborative nature of our workforce, we need to implement well-organized and strong operation processes to sustain the long term growth of the organization. During the internship, we will assign the candidate a business process redesign project, using the understanding of cross-functional team dynamics, information technology and knowledge integration. The candidate will become familiar with the current processes of the organization and select one area to form the basis of the research. The outcome of this project is a presentation on best practices for successful cross-functional team processes in a contemporary business and recommendations for efficiency and efficacy around the selected area of operations.

Creating Nail Laminated Mass Timber Panels using Trembling Aspen and Lignoloc wooden nails

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