Innovative Projects Realized

Design and development of an automated indoor position tagging system and autonomous navigation for a contact-based flying robot using sensor fusion and machine vision

Providing three-dimensional (3D) coordinates and more importantly drone navigation in GPS-denied environments has been always challenging. Limiting factors such as signal reflection from walls (multipath), lack of Global Positioning System (GPS) signals in confined spaces and non-line of sight (NLoS) communication with orbiting satellites, build a barrier to navigate indoor drones. In this work, we propose to add a navigation feature to Avestec’s tethered-drone along with extracting the 3D coordinates of the drone with centimeter accuracy while flying inside metallic enclosed spaces. These features include inspection data tagging and eliminating the entrance of human operators in confined environments by providing assistance to (semi-) autonomous navigation.

Matières secondes – Valorisation du rejet industriel

Comment redonner la juste valeur aux matières résiduelles issues de la production des objets?

Le projet est une collaboration entre le fabricant de luminaires Lambert et Fils et l’équipe de recherche de Guillaume Sasseville, professeur en design des objets à l’École de Design de l’UQAM.

Le projet consiste à concevoir, à analyser les opportunités et les impacts de la mise en place d’un écosystème interne de recyclage circulaire des matières résiduelles en réintégrant celles-ci dans la fabrication de nouveaux luminaires. Un thème sous-jacent au projet consiste à explorer l’esthétique de la viabilité environnementale. Il est proposé ici de considérer les variations propres aux matières recyclées comme des opportunités participant au langage formel des objets.

Development of an integrated CO2 capture and conversion system for methanol, DME and ethanol production

The main objective of this project is to design an effective CO2 capture and conversion technology for alcohols and DME production. The process is based on microwave-assisted CO2 adsoprtion process integrated with hydrogen and syngas. The modelling of the novel microwave adsorption system will be performed. The process simulation tool will be provided to determine the properties of the products and operating conditions of each section. Moreover, the energy consumption and specifications of the microwave heating system from the flow data and other operating conditions will be defined. This system will be integrated with the CO2 conversion process to By incorporating the practical data provided by SyncoBiofuels, the equations describing the phenomena, including movement, mass and energy transfer equations, and Maxwell’s equations, will be solved using the simulation model.

Adult Third Culture Kids’ (ATCK) Concept of Belonging and Identity Creation: Can Spiritual Self-Leadership be a Solution?

Adult Third Culture Kids (ATCKs) are adults who have been shaped by their mobility and cross-cultural experiences as a result of spending a significant part of their developmental years in a country other than their passport country. Although these experiences have provided ATCKs with valuable characteristics and skillsets, ATCKs struggle with identity creation and a sense of belonging which can detract from their development, both personally and professionally. This study will explore the impact of inner life and spiritual self-leadership by investigating the question “How can spiritual self-leadership encourage identity development and sense of belonging in ATCKs in order for them to fully realize their potential and value contribution in the workplace?” Although this proposed research focusses on ATCKs, the impact could be felt by other demographics who have had similar experiences, such as immigrants, second generation immigrants, expatriates, and bi/multi-cultural adults.

Machine learning methods for automatic diagnosis, severity assessment, prognosis, and disease understanding of COPD

Chronic Obstructive Pulmonary Disease (COPD) is a progressive, debilitating, chronic respiratory disease that affects 600 million people worldwide and is responsible for 3 million deaths worldwide each year. Given the recent advances in artificial intelligence (AI) and the availability of large datasets from both the public and private sectors, our project applies AI to analyze large-scale medical datasets and develops tools capable of performing accurate diagnosis, severity assessment, and prognosis of COPD. Working in parallel, our project also aims to use AI to identify relevant biological markers that can predict current disease status and future progression. Ultimately, the tools developed and experimental results obtained throughout our research period will guide our partner organization in developing protocols for drug target discovery and validation, as well as therapy evaluation.

Projet de recherche : Etude de la relation entre pression artérielle à l’effort et performances cognitives

La préservation des fonctions cognitives constitue un enjeu majeur de santé publique au Canada dans un contexte de vieillissement démographique. Cette évolution s’accompagne d’une augmentation des maladies cardiovasculaires, souvent liées à l’hypertension artérielle, ainsi que des troubles neurocognitifs. Or, leur détection repose fréquemment sur des évaluations réalisées à des stades avancés, limitant les possibilités d’intervention précoce. Il est donc nécessaire d’identifier des prédicteurs simples, accessibles et fiables de la performance cognitive.

Plusieurs travaux ont montré que la rigidité artérielle (Joly, 2017) et la capacité cardiorespiratoire (Ahmadi & Mekari, 2024 ; Predovan et al., 2021) sont associées aux performances exécutives. Cependant, leur mesure nécessite des équipements spécialisés, parfois peu adaptés à la pratique de terrain.

Dans cette perspective, la pression artérielle à l’effort apparaît comme un indicateur particulièrement pertinent. Moins influencée par les conditions environnementales que la PA au repos (Lund-Johansen, 2002), elle a déjà été identifiée comme prédicteur du développement des maladies cardiovasculaires (Idzik et al., 2024 ; Schultz et al., 2026), elles-mêmes associées au déclin cognitif et à la démence (Harrison et al., 2014). Son étude représente ainsi une piste prometteuse pour identifier un prédicteur simple des performances cognitives.

Demande pour un projet de modélisation et analyse de la dynamique des écosystèmes forestiers face aux incendies

Les forêts canadiennes sont de plus en plus vulnérables aux incendies, sous l’effet des changements climatiques et des pratiques de gestion traditionnelles. Le projet Pyrosilviculture explore des approches de sylviculture adaptative pour améliorer la résilience des forêts face aux perturbations liées au feu.
L’objectif est de développer et tester des méthodes pyrosilvicultures capables de gérer efficacement la biomasse combustible tout en préservant les services écosystémiques et la biodiversité. Ces méthodes intègrent une gestion multi-objectifs pour évaluer l’efficacité des interventions sur la santé et la résistance des forêts.
Le projet mettra en place deux sites de démonstration au Québec pour tester, implémenter et suivre ces pratiques. Les résultats permettront d’évaluer comment la sylviculture adaptative peut réduire les risques d’incendie, optimiser la gestion de la biomasse et soutenir la durabilité des écosystèmes forestiers.
En combinant recherche appliquée et démonstration sur le terrain, la pyrosilviculture vise à fournir des solutions scientifiques concrètes pour des forêts plus résilientes et une gestion forestière innovante.

Une approche formelle pour détecter et corriger des incohérences opérationnelles dans les architectures microservices

La définition d’un niveau de service réalisable pour les systèmes d’information contemporains est une activité complexe. L’utilisation d’architectures logicielles granulaires, comme celle de microservices, demande une analyse locale et globale des capacités de chaque composante d’un système informatique. L’analyse manuelle des profils opérationnels de ces composantes par un expert humain rencontre des limitations cognitives. En effet, tracer le portrait des interactions entre des centaines, voire des milliers de services composant de multiples systèmes d’information manuellement est un défi actuel. Cela entraîne souvent des incohérences, voire des contradictions, dans les objectifs de niveau de service du système et des actions de stabilisation pouvant être mises en place par les différents services le constituant. Dans ce projet, nous nous intéressons à la détection et à la correction de ces incohérences.

Ce projet répondra à cette problématique, premièrement, par la définition formelle du profil opérationnel des composantes d’un système d’information, notamment les propriétés liées à la cohérence, deuxièmement, par un ensemble d’algorithmes permettant d’identifier si des incohérences existent, et enfin par un algorithme d’optimisation permettant de corriger l’incohérence trouvée. Les résultats attendus représenteront un gain important en gestion de services informatiques et en prévention des instabilités, pouvant bénéficier à plusieurs organisations canadiennes.

Model Application for Estimating Total Suspended Solids in Eastern Amazonian Waters

Suspended sediments influence water quality, ecosystem functioning, and navigation in rivers and coastal environments. In the Eastern Amazon, estuarine systems such as the Guamá River and Guajará Bay experience intense variability in suspended sediment concentrations due to the combined effects of river discharge and tidal dynamics. These processes produce changes in water turbidity and optical properties, making continuous monitoring challenging using field measurements alone.
This project aims to improve the estimation of Total Suspended Solids (TSS) in Amazonian coastal waters by integrating satellite remote sensing, in situ observations, and machine learning techniques. Multispectral satellite imagery will be combined with field-based TSS measurements to develop models capable of capturing the optical and hydrodynamic complexity of tide-dominated environments.
By explicitly accounting for tidal influence and optical variability, the project addresses key limitations of existing TSS monitoring approaches, which are often developed for river-dominated systems.
The results will include multi-temporal maps of suspended sediment distribution, providing valuable information for environmental monitoring, water resource management, and navigation planning. The project also strengthens international collaboration and develops transferable methods applicable to other dynamic coastal and estuarine systems.

Multi-Objective Optimization for path planning: Comparing MOAstar to MOACO, older adults case study

As populations age, many older adults face increasing difficulty moving safely and comfortably through their cities due to challenges such as limited walking endurance, steep slopes, poor lighting, and the need for regular rest. This project aims to improve pedestrian route planning by developing and comparing methods that generate routes adapted to older adults’ needs, considering factors such as distance, slope difficulty, and access to rest amenities. By testing these approaches on real urban environments in different countries, the project will contribute to safer, more comfortable, and more inclusive mobility for older adults. At the same time, it will strengthen the participating institutions’ expertise in intelligent transportation systems and data-driven urban mobility, support the training of highly qualified researchers, and advance research on inclusive, age-friendly mobility solutions.

Developing a User-Friendly Digital Platform for Coastal and Conservation Guardian Volunteers

This project will be conducted in collaboration with Island Nature Trust (INT) to develop a user-friendly digital platform for volunteers in their Coastal Guardian and Conservation Guardian Programs. Currently, the organization faces an innovation challenge in coordinating and supporting a geographically dispersed network of volunteers, many of whom have limited technical experience. Also, existing processes for scheduling, training, data collection and communication rely on multiple platforms and manual updates. The new platform will centralize these functions into a single, accessible hub where volunteers can access training materials, submit surveys, share photos, coordinate schedules, and view interactive maps highlighting priority sites. By streamlining volunteer engagement and program coordination, this project strengthens community participation and improves conservation outcomes.

Lowering Costs in Biotherapeutics: Raman Spectroscopy for Real-Time Antifoam Detection in Perfusion Bioreactors

This project aims to improve the production of monoclonal antibody (mAb) based medicines by developing a novel method for measuring antifoaming agents within perfusion bioreactors used to produce mAbs. Antifoams are necessary to keep bioreactors running smoothly, but they are also widely believed to contribute to reactor membrane fouling, which increases costs and severely limits how long these manufacturing systems can operate. During the placement, the intern will work with the host institution to develop and validate a Raman spectroscopy–based method to measure antifoam concentrations in real time, then bring this method back to the home institution for use in ongoing perfusion bioreactor research. The project benefits the host institution by applying its advanced analytical expertise to a new and practical manufacturing challenge, while the home institution gains new analytical tools, trained personnel, and transferable methods that strengthen its continuous biomanufacturing research capacity. Together, this collaboration supports more efficient bioprocess development and contributes to long-term improvements in biologics manufacturing research.