Innovative Projects Realized

Urban Air Mobility Digital Twin for Safe Air–Ground Operations in Montreal

This project aims to develop and test a “digital twin” (a realistic virtual copy) of an Urban Air Mobility system, such as air taxis operating in a city, to support safer and faster operational decisions. Using a simulated city environment of Montréal and realistic flight scenarios, the project will model key elements such as vehicle routes, traffic rules, takeoff/landing sites, and disruptions (weather, delays, or congestion). It will then integrate prediction and conflict-avoidance capabilities so the system can anticipate risky situations and recommend practical actions (for example, rerouting or holding at a waypoint). The expected benefits are improved safety and reliability, better traffic coordination, and clear guidance on what level of model detail is needed to support time-constrained decisions, helping accelerate the future deployment of Urban Air Mobility services.

Design and Implementation of an Experimental Setup to Characterize Energy Storage in Water Reservoirs

Ce projet vise à concevoir et mettre en place un montage expérimental destiné à caractériser le stockage d’énergie dans des réservoirs d’eau. L’objectif est de mieux comprendre les phénomènes hydrodynamiques associés au remplissage, à la vidange et au comportement transitoire de ces réservoirs dans un contexte de stockage d’énergie. Le stage se déroule au Département de génie mécanique de l’Université de Sherbrooke, sous la supervision du Pr. Alla Eddine Benchikh Le Hocine.
Le travail consistera à développer un dispositif expérimental permettant de mesurer les écoulements, les pertes de charge et les variations d’énergie potentielle au sein du réservoir. L’étudiante contribuera également à la collecte et à l’analyse des données, ainsi qu’à la validation de modèles physiques utilisés pour décrire ces phénomènes. Les résultats attendus permettront d’améliorer la compréhension des systèmes de stockage d’énergie basés sur l’eau et d’orienter la conception de solutions plus efficaces.
Ce projet s’inscrit dans une démarche de recherche appliquée visant à optimiser les technologies de stockage d’énergie hydraulique, un enjeu important pour la transition énergétique.

Developing EELS Methodologies for the Characterization of Next-Generation Plasmonic Materials

Localized surface plasmon resonance underpins numerous applications, including plasmonic sensing, energy conversion, and cancer therapy. However, understanding how structural and compositional factors govern plasmonic resonances in increasingly complex sample architectures is challenging. Electron energy loss spectroscopy (EELS) in transmission electron microscopy (TEM) is a powerful method for probing electronic characteristics of plasmonic materials at the nanoscale, but it is often limited by two main challenges: (1) achieving sufficient energy resolution to observe low-energy resonances, and (2) incompatibility with air- and electron-beam-sensitive nanoparticles. This project proposes advanced 2D/3D EELS techniques that preserve both spatial and energy resolution while minimizing sample degradation. The University of Cambridge provides an ideal environment for this work, with extensive experience in 2D/3D EELS imaging and access to a world leading monochromated TEM with an inert-transfer cryo holder. This world-class platform is perfectly suited for investigating the geometric and compositional heterogeneity influences on the plasmonic behavior of novel ambient/e-beam unstable plasmonic group IV nitride (TiN, ZrN) and their hetero-nanostructure (TiN@porous SiO2). The developed methodology will enable comprehensive sub-nanometer characterization, providing unprecedented insights into structure-plasmonic property relationships.

Prédiction des interactions médicament–cible dans le paludisme à l’aide de réseaux de neurones sur graphes et d’apprentissage profond

Le paludisme, aussi appelé la malaria, est l’une des maladies infectieuses les plus meurtrières au monde. Elle est causée par le parasite protozoaire Plasmodium. Malgré les avancées significatives dans la compréhension de ce parasite, plusieurs enjeux persistent, notamment le développement de résistances aux traitements antipaludiques actuels. Cette problématique renforce l’urgence de découvrir de nouveaux composés capables de cibler des mécanismes biologiques encore peu exploités chez Plasmodium.

Dans ce contexte, les approches de Drug–Target Interaction (DTI) constituent une alternative complémentaire et pertinente aux approches phénotypiques traditionnelles. Elles visent à prédire explicitement l’interaction entre une molécule candidate et une protéine cible spécifique, permettant ainsi d’associer l’activité d’un composé à un mécanisme biologique précis. Cependant, la prédiction des interactions médicament–cible demeure un défi complexe. Les diversités et complexités des structures des molécules et des protéines parasitaires rendent la modélisation de leurs interactions délicate.

Les récents progrès de l’intelligence artificielle, notamment l’émergence des Graph Neural Networks (GNN), offrent de nouvelles perspectives dans le cas du paludisme avec une modélisation explicite des interactions médicaments-cible.

L’objectif principal de ce projet est de développer un modèle de DTI sur les GNN pour prédire efficacement les interactions entre des antipaludiques candidats et des protéines cibles de Plasmodium falciparum.

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.

Coexistence with large felids in the Calakmul region: a systemic approach to understanding livestock producers’ viewpoints, barriers, and motivations

Big cats, such as jaguars and pumas, play an important role in ecosystems. But the expansion of pastureland for livestock is destroying and fragmenting their habitat, increasing conflicts with farmers. Some farmers still use illegal lethal methods, even though non-lethal techniques can limit attacks by big cats on livestock.
The jaguar (Panthera onca) is near threatened globally and endangered in Mexico. The Yucatán Peninsula is home to the world’s second-largest population of jaguars. In the Calakmul region, jaguars and pumas cause 15% and 22% of livestock attacks, respectively, with the majority caused by jaguars. Among the farmers surveyed, 89% have lost animals, with a median of five losses over two years.

Some protection techniques, such as visual and audible devices, can work, but their adoption depends on economic, social, cultural, and psychological factors.

To promote coexistence, we want to answer two questions: 1) Do visual and audible devices cause fear or avoidance in felines? 2) What are the perspectives, obstacles, and motivations of ranchers? Understanding this will help us propose appropriate solutions and encourage human-feline coexistence.

L2M – Scalable and Green Nano-manufacturing of Graphene and 2D Nanomaterials for Energy and Consumer Technologies

The proposed project focuses on commercializing a proprietary manufacturing technology called Compressible Flow Exfoliation (CFE) for producing high-quality 2D materials like graphene and boron nitride. Traditional production methods, such as chemical exfoliation, are slow, expensive, and generate significant toxic waste, hindering widespread industrial adoption. The CFE method offers a sustainable, physics-based alternative that allows for continuous, high-speed production suitable for scalable applications in electronics and construction. This project will validate market demand, develop a comprehensive financial model, and establish an intellectual property strategy to prepare the technology for investment and pilot implementation.

L2M – Astaxanthin-secreting probiotic

A novel astaxanthin-secreting microorganism has been developed as a part of the intern’s graduate research focus. This technology has applications primarily in the aquaculture and nutraceutical industries. In aquaculture, it can be used to better deliver astaxanthin, an essential nutrient, to salmon and trout compared to current methods. This technology has the potential to reduce costs for aquaculture farmers, as astaxanthin alone makes up 30-40% of total feed costs; improve the health, resilience, and quality of the fish; and is more sustainable that current astaxanthin sources.

The Lab2Market Launch project aims to translate this technology-based innovation into a commercially viable solution for the Canadian aquaculture industry. The primary objective is to build the business, regulatory, and commercialization expertise required to move beyond proof-of-concept and toward market readiness. The Lab2Market Launch will provide interns with structured training and expert mentorship. Through weekly workshops, one-on-one coaching, simulated board meetings, and peer learning, interns will refine their target market, validate customer needs, develop a go-to-market strategy, and evaluate pricing and scaling models. The program will also strengthen intherns’ leadership and entrepreneurial skills while connecting interns with industry stakeholders and potential partners. By the end of the Lab2Market Launch program, the interns’ technology innovation will have a clearly defined commercialization pathway, a validated business model, and a strategic roadmap to bring a low-cost, sustainable astaxanthin to the aquaculture industry.

Base évolutive de données du Registre des entreprises du repreneuriat du Québec

La stratégie de l’entreprise est de moderniser le système de gestion de la relation client (GRC) à terme, en commençant par explorer l’ajout de données secondaires externes en temps réel et ainsi mieux cibler les clients potentiels. Le partenaire doit développer une stratégie innovatrice permettant d’identifier, en amont, les futurs clients afin de les accompagner plus tôt dans le processus de transfert d’entreprise en mobilisant des sources d’information secondaire externes à l’organisation. Le projet déterminera la faisabilité d’utiliser un jeu de données du Registraire des entreprises du Québec.

Photo-Assisted Electrodes for Hydrogen Production & Energy Storage

Hydrogen is expected to play a key role in Canada’s transition to a clean and sustainable energy system, but current hydrogen production technologies still face challenges related to efficiency, durability, and cost. This project explores a new approach to improve hydrogen production and energy storage by combining light-responsive semiconductor materials with electrochemical devices.

The research focuses on designing advanced electrodes that can absorb light and use that energy to assist electrochemical reactions. When light shines on these semiconductor layers, additional electrical charges are generated that can help drive hydrogen production from water more efficiently and reduce energy losses. By carefully selecting and layering organic and inorganic semiconductor materials, the project aims to improve how charges move through the device and how long the electrodes can operate without degradation.

Using scalable fabrication techniques and advanced characterization tools, the project will evaluate how material choice, layer thickness, and device structure influence performance under realistic operating conditions. The results will support the development of more efficient, durable, and cost-effective hydrogen technologies that are compatible with large-scale manufacturing.

This research contributes to Canada’s clean-energy goals by advancing innovative hydrogen production methods, strengthening international collaboration with Brazil, and training highly qualified researchers in emerging energy technologies.

L2M – Launch – Path Forward Neurotech

Path Forward Neurotech is commercializing AR-based cognitive-motor training for seniors in residential care. This Lab2Market Launch project executes B2B sales to long-term care facilities, validating pricing models and building repeatable sales infrastructure from 60+ validated customer discovery interviews.

L2M – Ultrafast Photocurrent Spectrometer (UPCS)

This project focuses on supporting the commercialization and market entry of a new scientific instrument called Ultrafast Photocurrent Spectrometer. To control the semiconductor material quality, and to test semiconductor device performance, ultimately leading to superior device efficiency and yield, the semiconductor industry needs a critical tool to characterize the electrical figures-of-merit when devices are in operation. The electrical figures-of-merit include carrier lifetime, mobility, and defect concentration, etc. Existing commercialized time-resolved spectrometers (TRS) including the time-resolved photoluminescence (TRPL) and transient absorption (TA) spectrometers are limited to the carrier lifetime measurements by the identification of semiconductor optical property, rather than electrical property. As a result, they lack one of the most critical parameter measurements: carrier mobility. Moreover, due to the complexity of the semiconductor device structure, those TRS are limited to the characterization of semiconductors only. Thus, despite that these approaches have provided a glimpse into semiconductor photophysics, a significant gap remains in characterization of electrical figures-of-merit in operando, i.e. when devices are at work. We aim to address this challenge by developing a new generation of time-resolved spectrometers: the ultrafast photocurrent spectrometers (UPCS). The UPCS have the following unique features: 1) a complete electrical figures-of-merit characterization including carrier lifetime, mobility, and defect concentration, 2) in-operando device characterization, and 3) a wide range of temporal and wavelength coverage. Although the UPCS has been successfully demonstrated in a research setting, this project will help translate it into a market-ready product by identifying the right target customers, understanding their needs, and developing a go-to-market strategy.