Innovative Projects Realized

Simulation-Based Factory Layout Design and Workflow Optimization for Offsite Construction

Off-site construction involves prefabricating building components in a controlled environment, allowing for enhanced efficiency, quality, and sustainability. This research addresses critical challenges in the development of manufacturing facilitylayoutsfor Roberts Group, Prince Edward Island(PEI). By employing digital simulation approaches, the project aims to design and optimize factory layouts and workflows, reducingmaterial and
streamline production processes to support modular building components. The project responds to PEI’s housing crisis, where demand for affordable housing. The anticipated production of over 200 modular units annually will directly contribute to meeting local housing needs. The collaboration with the University of New Brunswick’s Off-
site Construction Research Centre will generate best practices and methodologies that can be scaled across the industry. This project not only supports Roberts Group’s immediate operational goalsbut also establishes transferable frameworks for sustainable off-site construction.

Interactions entre la végétation boréale alluviale et la dynamique fluviale en contexte de pergélisol sur la Beaver Creek River, Yukon

Ce projet de recherche vise à étudier les impacts du changement climatique sur la Beaver Creek River, au Yukon, au Canada. Dans cette région froide, le pergélisol (sol gelé en permanence) se dégrade sous l’effet de l’augmentation des températures, particulièrement marquée aux niveau des pôles, ce qui peut fragiliser les berges des rivières, modifier les écosystèmes et affecter les infrastructures humaines. A l’aide de photographies aériennes, d’images satellites, d’observations sur le terrain et d’analyses sédimentaires en laboratoire, le projet étudie les changements survenus au cours des 60 dernières années. Les résultats aideront par exemple à déterminer si la végétation, qui se développe à mesure que le pergélisol dégèle, stabilise les berges ou, au contraire, contribue à leur érosion. Sur le plan scientifique, il apportera de nouvelles connaissances sur les impacts du réchauffement climatique dans les régions périglaciaires, qui représentent une zone sensible et relativement peu étudiée. Les résultats pourront être utilisés pour mieux anticiper les risques liés à l’érosion, aux inondations et à la dégradation des écosystèmes au niveau de ces rivières arctiques. Pour les gestionnaires et décideurs locaux, ces informations seront utiles pour réfléchir à l’entretien de certaines infrastructures, comme l’Alaska Highway.

Applied Transformative Justice Frameworks for Gender and Sexuality-Based Violence Prevention

This project involves conducting a literature review of research and popular publications on transformative justice—an approach that aims to develop responses to violence by understanding the structures of inequality outside of the current pathways of criminalization and punishment—with the aim of developing applied tools, resources, and guidelines for distribution as open access resources in both English and French on gender- and sexuality-based violence prevention. The project builds on a university-community partnership between
Éduconnexion and Concordia’s Simone de Beauvoir Institute to create a hub for resources to support and empower community organizations in under-resourced areas throughout the city of Montreal in using transformative justice approaches in their work with communities. Built out of a commitment to agency, cultural safety, and self-determination, the project centers on an understanding of the intersections between race, gender, sexuality, citizenship status, religion, ethnicity, disability, and other factors shaping the experiences of
people who are at risk of experiencing or witnessing gender- and sexuality-based violence.

Évaluation du potentiel de croissance du mélèze hybride et laricin en région boréale

Le mélèze laricin (Larix laricina) serait une espèce intéressante pour la production de matière ligneuse (Bolghari and Bertrand, 1984). Dans les années 70, un programme d’amélioration génétique a commencé et l’hybride (L. ? marschlinsii Coaz.) entre le mélèze d’Europe (L. decidua) et le mélèze du Japon (L. kaempferi) s’est avéré très performant (Perron, 2011). Cependant, contrairement au mélèze indigène capable de pousser sur une large gamme de stations (Tilton, 1976), les espèces exotiques seraient à éviter sur les sites trop humides en raison des risques de gel tardif (Robbins, 1985). Leur utilisation en région boréale n’a jamais été évaluée et il convient d’étudier le potentiel des plantations de mélèze hybride à cette latitude et de les comparer aux espèces indigènes. Pour cela, nous allons mesurer, analyser et comparer la croissance du pin gris, de l’épinette noire, des mélèzes laricins et hybrides implantés en 2007 dans un dispositif de recherche localisé dans la région écologique 5a.

Estimating brain tissue deformation from a microscope video

Epilepsy, a neurological disorder impacting millions worldwide, often requires precise surgical interventions when medications fail. The surgical procedure demands high levels of skill to remove the lesion causing epilepsy while minimizing damage to surrounding healthy tissues. Current training methods for such intricate procedures are insufficient, relying heavily on subjective assessments and limited hands-on opportunities, which have further decreased due to restrictions like reduced duty hours and the COVID-19 pandemic.
This project builds on a previously validated simulation prototype that uses calf brains to mimic the mechanical and anatomical properties of human brain tissue. The platform employs a tracking system to collect quantitative data during procedures. However, it lacks the ability to measure one of the most critical performance metrics: the force exerted by surgical instruments on brain tissue. To address this, the project introduces a novel sensorless estimation method, leveraging high-resolution optical cameras and biomechanical modeling to infer contact forces from tissue deformation observed in real-time.
This project will provide a cost-effective, realistic training solution to address gaps in neurosurgical education, enhancing skill acquisition, reducing errors, improving patient safety, and advancing competency-based surgical education.

Développer un modèle bioéconomique pour la durabilité de la filière bovine au Québec

Développer un modèle bioéconomique pour la durabilité de la filière bovine au Québec

EcoFusion : biocomposites innovants à base de biochar et PLA

Le projet de recherche proposé a pour but de développer de biocomposites durables en combinant l’acide polylactique (PLA) et le biochar, un matériau issu de la pyrolyse de résidus forestiers. Face aux enjeux environnementaux liés à la pollution plastique, ce travail cherche à apporter des solutions, à la fois innovantes et durables, pour la conception de matériaux biodégradables et économiquement viables. Par ailleurs, le PLA, un plastique biosourcé, présente des avantages environnementaux notables tels qu’une faible consommation énergétique pour sa production et une meilleure biodégradabilité par rapport aux plastiques pétrochimiques. D’autre part, l’ajout de biochar vise à améliorer ses propriétés tout en garantissant la performance environnementale du composite. De plus, le biochar, grâce à sa structure poreuse et sa composition élémentaire, présente un potentiel rôle fertilisant en permettant notamment le maintien des nutriments dans les sols.

Elustros Seating App Development

Ellustros has developed an App and SMART Chair to provide an automated ergonomic office solution using AI and IoT technology. The app uses real-time data to assess optimal posture and automatically adjust the SMART Chair to ensure comfort, efficiency, and reduce the risk of injury. At this stage of the product development, the business model requires an independent assessment of the tros.ai App. The App uses standard methods and AI to determine seating, desk and monitor dimensions that it collects from photos taken from a mobile phone camera. The use of AI in ergonomics is new to the field and allows other body features to be included in the process. As a precursor to integrating with the SMART chair, the purpose of the application is to test the App outputs against “standard” ergonomic rules for seating and office set up and personal preferences (which may not be appropriate). We plan to capture anthropometrics (body shape & size) from 100 diverse male and female individuals from the McMaster University community. We will test the software against a set up purely based on individual anthropometrics and comfort.

Forecasting for Default Recovery

The proposed project aims to harness the power of Artificial Intelligence (AI) and machine learning to develop a predictive model that assists in predicting delinquency in financial contexts. By integrating AI and predictive modelling approaches, the project seeks to enhance the accuracy, efficiency, and interpretability of delinquency predictions within the residential mortgages space. The focus will be on creating robust predictive models using advanced ML and AI techniques, including gradient boosting machines like XGBoost, survival analysis models for time-to-event predictions, and stochastic processes to model transitions between delinquency categories.

Unpublished Works for Cello Solo of the Mexican Avant-garde

My research project into Mexican Avant-garde music for solo cello (written between 1962 and 2012) attempts to define and evaluate what Mexican Cello Solo Music is and how it has evolved over the years to the point of exerting a significant influence on the universal cello solo repertoire. (This discipline belongs to a category of understudied fields and so far has no available literature on the subject) I have been privileged to discover these new works (approximately 20 pieces in all) many of which have yet to be published, or for that matter, adequately exposed to the public. My project provides me with the opportunity to describe and analyze these new works while simultaneously making important comparisons to the works that comprise the standard opus of great composers from western cultures, creating the first formal introduction to Mexican Cello Solo Music. My goal is to keep the performance of this repertoire alive in the concert hall to wider and varied audiences.

Developing Low-Power Spiking Neural Networks for Image Enhancement on Embedded Neuromorphic Boards: A Multimodal Sensor Fusion Approach

Image enhancement consists of creating a composite image (fused image) from different sources. The objective of this project consists of acquiring images from Electro-Optical sensors and Infrared (IR) sensors in low light conditions, to enhance them, to combine (fuse) them in order to create an image of better quality. To do so, the project will focus on establishing the fundamentals steps to develop Spiking Neural Networks (resources, tests and activities to develop a complete prototype), with very low consumption for embedded neuromorphic boards for an image-enhancement use case.

Statistical Shape Modelling in Ankle Osteoarthritis

Osteoarthritis (OA) is a degenerative joint disease causing pain and disability affecting weight-bearing joints. Unlike knee and hip OA, ankle OA is linked to trauma and remains under-researched despite its impact on mobility and quality of life. Joint kinematics play a key role in OA progression, as altered movement patterns accelerate cartilage degeneration by changing localized stress. Computational techniques like Discrete Element Analysis (DEA) estimate cartilage stress using accurate joint morphology, but cartilage geometry acquisition is limited by MRI’s cost and accessibility.

This project addresses this challenge using Statistical Shape Modeling (SSM) to predict cartilage distribution from bone shape. SSM identifies 3D geometric patterns across populations, linking tibia and talus bone shapes to cartilage geometry via statistical regression models. High-resolution CT scans and MRI datasets will train the SSM to predict cartilage thickness and distribution, bypassing the need for direct soft tissue imaging.

The predicted cartilage geometry will integrate into DEA models, enabling simulations of joint mechanics. By combining SSM and DEA, this research offers new insights into ankle OA progression, improving diagnosis, personalized treatments, and outcomes. This multimodal approach bridges a critical gap in understanding the interplay between bone shape and cartilage health in OA.