Projets novateurs réalisés

Ex Vivo Live Imaging of Hematopoietic Stem Cells in D. melanogaster

This project aims to investigate asymmetric cell division (ACD) in blood cell development using live imaging and Drosophila melanogaster (fruit fly) as a model system. Hematopoiesis, the process of blood cell formation, relies on tightly regulated mechanisms to balance stem cell self-renewal and differentiation. Disruptions in this balance can cause blood disorders such as leukemia. ACD, where a stem cell divides to produce one self-renewing and one differentiating daughter cell, is a key mechanism for maintaining this balance, but its role in mammalian hematopoiesis remains poorly understood due to technical challenges in live imaging. This project will combine advanced live imaging techniques with genetic tools for tracking ACD-associated proteins in the Drosophila lymph gland, a hematopoietic organ. By visualizing how cell polarity proteins like Par-6 dynamically influence ACD and blood cell fate in real-time, the study aims to provide insights into how environmental signals regulate blood cell development and identify potential therapeutic targets for blood disorders.

Study to increase production efficiency in a lumber recycling process

This project promotes the use of recycled material by diverting it from current waste streams, thus reducing the pressures on local landfills and positively contributing to a reduction in greenhouse gas emissions. However, processing lumber waste generated in construction and demolition projects remains challenging due to the variability in dimensions and wood species as well as the presence of contaminants (e.g., coatings and preservatives) and impurities (e.g., nails and screws). As such, the goal of the project is to collect extensive data on the manufacturing process to study material flow and quantify the efficiency of each processing step in order to identify areas of improvements. The intern will then design novel solutions to significantly increase process efficiency. These solutions will be tested at a small-scale before selecting the best ones that will be implemented. The partner organization will benefit from the knowledge gained from the thorough data analysis and the implementation of novel solutions that will improve its efficiency and support its mission.

Full Scale Biological Filters: assessing backwash performance on microbial and organic carbon outcomes

The City of Ottawa operates two water treatment plants, Britannia and Lemieux Island Water Purification Plants. Their treatment consists of coagulation with alum, filtration and post-filter disinfection. The City operates its filters within a “biofiltration” framework intended to allow for the beneficial growth of friendly bacteria on the filter media surface. Biofiltration enhances removal of organics in the water system that may otherwise contribute to disinfection by-product formation. To allow filters to operate properly, filters are cleaned via a backwash step at regular time periods to clean and maintain the proper function of filters. This research aims to assess various methodologies to evaluate the health of filtration systems coupled with backwash operation. Due to plant maintenance, the Lemieux filter backwashing was supplemented with a chlorine wash. This project aims to evaluate whether a chlorinated backwash affects the organic removal performance at Lemieux WTP, investigate the presence and changes in the microbial population within the biofilter systems, and assess recovery times after transitioning from a chlorinated backwash to a standard water wash. This full-scale research study aims to provide valuable insights for the optimization of filtration systems and map out changes to microbial populations with chlorinated and un-chlorinated backwashes.

Numerical modeling of lean, premixed, pressurised hydrogen flames using large eddy simulation

Blending methane with hydrogen for power generation is well-known to significantly lower carbon-based emissions. However, studies have shown that implementing hydrogen is not trivial. In gas turbine combustion systems, major modifications may be required to facilitate the safe combustion of hydrogen and these modifications depend on numerical modeling.

Turbulent combustion modeling can strongly accelerate the time to implement decarbonised technology but industrial practices are typically validated and optimised for natural gas burning, These require thorough checks to ensure they can be used to model hydrogen-specific phenomena. For example, Hydrogen’s mass diffusion occurs at a higher rate relative to thermal (heat) diffusion, leading to flame instabilities at lean conditions. Pressure exacerbates these but research is scarce at gas turbine-relevant conditions.

This project will explore the usage of industrial models to investigate H2 flame dynamics under pressure. By comparing with publicly-available experimental data, modifications will be introduced to these models. The main objective of this project is to identify the limits of modeling hydrogen by current industrial methods, and then assess newer strategies that incorporate hydrogen physics more explicitly. This will result in clear recommendations for changes to industrial practices and enable the development of future injector technology.

Formalisation d’arguments de sécurité

S’inscrivant dans la continuité du premier stage, ce projet vise à unifier les langages de description de structures argumentatives GSN et TCL et à adapter la théorie de Dempster-Shafer au langage unifié. Cette théorie est la plus adéquate pour intégrer à une structure argumentative les évaluations de ses noeuds. Notre objectif est d’arriver à déterminer de bonnes règles servant à propager avec précision les évaluations des noeuds enfants vers le noeud racine. Le résultat des modèles d’inférence est très important pour l’entreprise partenaire, car l’interprétation de ces modèles en termes d’analyse de risques donne lieu à d’importantes prises de décisions. Ce travail aboutira à une meilleure définition des méthodes d’interprétation de structures argumentatives.

Antecedents and Outcomes of Workplace Mistreatment Experiences Towards LGBTQ+ Employees

This study is an ongoing project where data has been collected across four-waves using an LGBTQ+ sample. Using the available data, Isaiah will
support this project by creating a research model, developing hypotheses, and running the analyses for this project. Once the analyses have been
completed, Isaiah will assist in preparing a submission for the annual society for industrial-organizaitonal psychology (SIOP) conference held in April
2026. The submission/proposal will serve as a key deliverable of this project. Depending on the results of the study, the submission may be prepared for
potential publication to be submitted to an I-O journal.

Photodetection in quantum dots

The transformation of light in current, i.e. photodetection, has been exploited in several technologies. From the detectors used in materials characterization to solar cells, the use of performant materials that can efficiently produce photocurrents is inspired by the normal functioning of the eyes. Within them, a photon of light is converted into a current, traveling among neurons to reconstruct an image. When the photoreceptors in the retina do not operate properly, due to age-related or genetic diseases inducing the degeneration of the retina, a significant or complete loss of sight is associated with a lack of current treatments.
Artificially reproducing the functioning of the eyes can be accomplished by synthesizing artificial photodetectors. Inspired by the current interest in producing solar cells based on efficient photodetection materials, like the so-called perovskites, we propose the use of these materials for applications in biotechnology.
We will test perovskite nanomaterials synthesized through green protocols to study their effectiveness in photodetection. The synthesized quantum dots, nanomaterials capable of changing their optical response based on their size, will aim to replicate the photopigments in the eyes in terms of spectral range and sensitivity. The results of this project will have implications far beyond the envisioned application.

Demande de Stage MITACS à l’Université d’Oslo

Les prothèses myoélectriques permettent aux personnes amputées de contrôler un bras artificiel en captant les signaux électriques des muscles, appelés signaux électromyographiques (EMG). Cependant, ces prothèses restent limitées par des variations de ces signaux, causées par des facteurs comme la sueur, la fatigue ou le déplacement des électrodes, ce qui entraîne des pertes de précision et un besoin fréquent de recalibrage.

Mon projet vise à améliorer la fiabilité de ces prothèses en intégrant une nouvelle approche basée sur la mesure de l’impédance de la peau. Cette mesure permet d’évaluer la qualité du contact entre les électrodes et la peau, et ainsi d’ajuster intelligemment les algorithmes de reconnaissance des mouvements. En combinant ces données avec les signaux EMG, nous espérons rendre les prothèses plus réactives et stables dans des conditions variées.

En collaboration avec plusieurs centres de recherche, nous développons un prototype intégrant ces avancées. L’objectif est de créer une technologie plus robuste et facile à intégrer dans les prothèses existantes, afin d’améliorer l’expérience des utilisateurs au quotidien.

Utilizing Remote Sensing Technology for Blue Carbon Mapping in Coastal Ecosystems

The proposed project involves using advanced remote sensing technologies, such as optical imagery, Synthetic Aperture Radar (SAR), and LiDAR, to map and monitor blue carbon ecosystems like mangroves, seagrasses, and salt marshes. These ecosystems play a critical role in climate change mitigation by storing significant amounts of carbon. By focusing on Quebec’s coastal areas, the study aims to provide comprehensive maps of these habitats, estimate their carbon sequestration potential, and recommend the most effective monitoring techniques. The results will aid conservation strategies, policy-making, and the integration of these ecosystems into carbon credit markets, benefiting environmental agencies and coastal management authorities

Artificial Intelligence/Machine Learning Application in Formulation of Novel Material Compositions and Visualization Design for Intensive Outreach and Education for Denture and Anti-snore Devices

Denture assemblies are oral appliances or prosthetic devices to replace missing teeth and restore oral function, speech, and aesthetics. The dentures market is driven by the senior population and demand, which is expected to grow by 68% in the next 20 years according to the Canadian Institute for Health Information. This demographic also often suffer from sleep-related breathing disorders, such as obstructive sleep apnea (OSA), exhibiting moderate to excessive snoring which is often ignored or neglected. This neglect can increase the risk of more severe health problems such as stroke, hypertension, chronic heart failure, diabetes, and many others. The major components of denture assemblies, namely, gum, artificial teeth, and framework, including clasps, are often connected with adhesives or bonded with mesh or serrated surfaces that help keep the denture components assembled. The host supervisor of this proposed project is part of a group of researchers at Carleton University working with industrial collaborators to find innovative solutions for improved materials, manufacturing, and designs to address several issues relating to cost, durability, and convenience with the products that are in the market today.

Internship in Metabolic Engineering – Institute of Julich

This internship project focuses on developing optimized DNA sequences, known as signal peptides, to enhance the secretion of proteins produced by bacteria. Signal peptides are critical for secreting proteins out of the bacterial cell, facilitating their purification and downstream processing. Under the guidance of Dr. Susana Matamouros and Professor Michael Bott, a leading expert in microbial strain development, this project will integrate advanced techniques to identify, design and test signal peptides that improve secretion efficiency of selected target proteins, such as enzymes for plastics degradation. This work has the potential to contribute significantly to the development of innovative microbial production systems for industrially relevant biomolecules.
Potential objectives for the internship: 1) Identification of optimal signal peptides: test a library of signal peptides for their efficiency in enabling secretion of selected target proteins, such as cutinases or PETases in Corynebacterium glutamicum, a major microbial cell factory used in industry. 2) Use of the robotics platform of the institute for high-throughput strain development and for analyzing the recombinant strains for their efficiency in target protein secretion. 3) Develop approaches to improve the secretion capabilities of C. glutamicum by genomic mutations.

Social Media Audience Analytics Tool

Social media websites (e.g. Facebook, Twitter, etc.) are widely used by the general public and also by businesses to promote their product and services. Due to the nature of these websites, marketed content by businesses does not always reach their desired target. This can be improved by providing useful information to the businesses, such as the times their audience is using social media or their most active users. This information is not readily available, but can be derived by analyzing the available data on social media websites. This project aims at developing tools that will automatically provide this information to marketers to help them perform their marketing efforts more efficiently.