Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

30156 Completed Projects

2861
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5059
BC
812
MB
673
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842
SK
8957
ON
9368
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96
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579
NB
1120
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Projects by Category

Estimation de débits de crues saisonniers dans un contexte de changement climatique à l’aide des modèles d’apprentissage machine dans le Québec méridional

L’estimation des forts débits dans un contexte de changement climatique est une tâche essentielle à bien des égards pour notre société. Elle permet en l’occurrence d’analyser l’impact et les stratégies de mitigation face aux aléas naturels comme les inondations. Différentes approches ont été proposées pour répondre à ce besoin dont la modélisation hydro-climatologique (MHC) et l’analyse fréquentielle. Cependant, les effets du réchauffement planétaire ont intensifié le cycle hydrologique et ont restreint l’application de ces approches dites conventionnelles. De plus, la MHC fait également face à des incertitudes associées à la conception même des modèles climatiques, ainsi que hydrologiques (e.g., disponibilité de données, ou l’équifinalité et l’équiprobabilité du jeu de paramètres), sans mentionner l’expertise requise. C’est ainsi que ce projet s’intéresse à appliquer d’autres méthodes comme les modèles d’apprentissage automatique (ML) pour estimer la dynamique de ces forts débits en climat futur dans le Québec méridional, et ce en utilisant les derniers scénarios climatiques, ainsi que les indices climatiques caractérisant un événement d’inondation. Au niveau des retombées, le projet contribuera à l’avancement de l’expertise en matière d’applications des modèles de type ML au domaine des aléas naturels et l’évaluations des Plans de protection des territoires face aux inondations.

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Faculty Supervisor:

Alain Rousseau

Student:

Partner:

Universidad Nacional de Colombia

Discipline:

Engineering

Sector:

Artificial Intelligence; Water; Environmental Science and Technology

University:

Université du Québec : Institut national de la recherche scientifique

Program:

Globalink Research Award

Raman Quantification of Cancer Biomarkers for Early Lung Cancer

The intern will help Biomark Technologies to develop an new optical detection method, which is faster, less expensive and requires less expensive infrastructure by using Surface-Enhanced Raman spectroscopy (SERS), which will be suited to large scale market adoption. By the end of project, the intern will develop: 1) a SERS detection platform that is low cost and optimized for AcAm detection; 2) a data extraction approach that improve the sensitivity towards clinically relevant levels. During the project, the intern will be trained in the industrially relevant areas of optical systems and analytical biochemistry.

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Faculty Supervisor:

Reuven Gordon

Student:

Partner:

BioMark Technologies Inc (Richmond, BC)

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Victoria

Program:

Accelerate

Use of Metaheuristics for solving pricing problems arising from vehicle routing problems

The vehicle routing problem is a frequent real-world challenge, especially in transportation and logistics. It involves finding efficient routes for a fleet of vehicles to serve a group of customers while minimizing the overall travel cost. Methods for solving this problem exactly, meaning the solution found is guaranteed to be the best possible, are known to suffer from severe scalability issues even for moderate problems involving a few hundred customer locations, let alone real-sized problems which at times may contain several thousand customer locations. There is a known bottleneck in the exact methods for solving this problem, which involves a solution of a subproblem, that our project aims to address by using heuristic methods. If successful, this approach could significantly increase the size of the problems that can be solved exactly, which could lead to companies and other entities being able to reduce their costs associated with transportation. This project will enhance the research of the participating institutions in combinatorial optimization, a vital real-world field, and further solidify Montreal’s (Concordia’s hometown) position as a hub for this type of research. Additionally, it will promote collaboration between the host and home institutions, paving the way for future projects and research initiatives.

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Faculty Supervisor:

Claudio Contardo

Student:

Partner:

Pontifícia Universidade Católica do Rio de Janeiro

Discipline:

Computer science

Sector:

Education

University:

Concordia University

Program:

Globalink Research Award

An improved algorithm for the discrete ordered median problem

The ordered median is an important class of facility location problem that encompasses multiple other relevant location problems as particular cases. Deepening our understanding of this problem, its mathematical properties and proposing novel methodological contributions for its solution lies at the core of this project. We will consider a recent algorithm for this problem developed by the Principal Investigator and two collaborators in this project, recently submitted to a prestigious journal and currently in the second round of review. Improving this method to improve its scalability shall have a positive impact in the field of location problems. This could allow testing various hypothetical scenarios for a decision-maker in short periods of time. Potential applications of this research can be found in the location of hospitals, police stations, sensors, among many others. This research could also lead to the generation of other algorithms of a similar nature.

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Faculty Supervisor:

Claudio Contardo

Student:

Partner:

Pontificia Universidad Católica de Chile

Discipline:

Engineering

Sector:

Artificial Intelligence; Transportation (excluding aerospace)

University:

Concordia University

Program:

Globalink Research Award

The Politics of Drafting Decisions in International Organizations

Those who draft resolutions and treaties in international organizations (IOs) can significantly influence their content and acceptance. It is therefore puzzling that not all states are interested in drafting, so-called “pen-holding”. Veto powers Russia and China barely draft any United Nations Security Council (UNSC) resolutions, and in the African Union (AU), international bureaucrats or independent experts hold the pen. Why (not) hold the pen? Conceptualizing IO decisions as political tools, this project examines whether states draft IO decisions to control their content or to make a statement. States may avoid drafting roles because they prefer sovereignty over IO decisions. However, non-penholders face a dilemma: they can more easily veto or avoid implementing decisions they did not draft, but this diminishes the IO’s reputation, which might not be in their interest. Drawing on the interdisciplinary expertise of Dr. Nicole De Silva (Concordia University) and Dr. Anette Stimmer (University of St Andrews), the project examines decision-making in the UN and AU to discern the factors influencing states’ choices regarding pen-holding. Each research intern will focus on one international organization. Understanding the dynamics influencing IO decisions is important, as these decisions have significant implications for multilateralism in diverse issue areas of international relations.

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Faculty Supervisor:

Nicole De Silva

Student:

Partner:

University of St Andrews

Discipline:

Sociology

Sector:

Education

University:

Concordia University

Program:

Globalink Research Award

Annual Evaluation of the Effectiveness of a Family-based Childhood Healthy Lifestyle Program

Living a healthy life is really important to keep kids from becoming overweight and having long-lasting health problems. Generation Health (GH), is a 10-week program for families in British Columbia. Families can join inperson or through the internet. It has shown some good results in getting kids to exercise more and eat better since it started in 2018. Every year, the program gets checked to make sure it’s still working well and to make it even better. Our team is going to look at how well GH works in the real world and how it’s being put into practice. We will ask kids and parents questions before and after the program to see if it’s helping them be more active, eat healthier, feel better, and have a better life. This will help us understand the effectiveness of the program.

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Faculty Supervisor:

Sam Liu

Student:

Partner:

Childhood Healthy Living Foundation

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Victoria

Program:

Accelerate

Atmospheric cold-plasma modification as a sustainable clean technology for improving protein functionality, digestibility and tribological properties

With the increased global protein demand, it is necessary to effectively utilize protein extracted from plants, particularly with limited uses, which has poor digestibility and techno-functional properties. Therefore, the proposed project will aim at developing novel protein ingredients from alternative plant proteins with improved techno-functional properties using innovative, sustainable, nonthermal clean processing technology, thereby improving competitiveness and sustainability in protein industry.

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Faculty Supervisor:

Nandika Bandara

Student:

Partner:

University of Leeds

Discipline:

Life Sciences

Sector:

Education

University:

University of Manitoba

Program:

Globalink Research Award

Computation of inverted singlet-triplet energy gaps by machine learning enhanced computational chemistry methodologies

Ce projet est axé sur l’amélioration de la conception des matériaux, en particulier pour des applications telles que les diodes électroluminescentes organiques (OLED). Des modèles d’apprentissage automatique modernes et des méthodologies spécialisées en chimie quantique sont utilisés pour enquêter systématiquement sur ces matériaux. L’initiative consiste à établir un ensemble de données complet issu d’une sélection minutieuse de matériaux connus, servant de base à la formation de modèles avancés d’apprentissage automatique. Cette approche accélère l’identification de matériaux présentant des applications prometteuses pour les OLED et optimise les routines de simulation en chimie quantique existantes, réduisant ainsi les coûts computationnels. De plus, les méthodologies développées sont conçues pour s’étendre au-delà des OLED, contribuant à l’étude efficace de matériaux divers, tels que ceux utilisés dans les panneaux solaires. L’objectif principal est de rationaliser et d’améliorer le processus de conception des matériaux, favorisant l’efficacité et l’applicabilité dans divers domaines.

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Faculty Supervisor:

Rodrigo A. Vargas-Hernández

Student:

Partner:

Universidad Nacional Autónoma de México

Discipline:

Physics

Sector:

Education

University:

McMaster University

Program:

Globalink Research Award

Design and evaluation of congestion control algorithm for fluctuating bandwidth at extreme condition scenarios of 5G-advanced and 6G mobile networks

The applications of the future will require support for ultra-low delay, high bandwidth, and multiple data streams into the gigabit-per-second range. 5G-Advanced and 6G networks with the assumption that width bandwidth will be available through the utilization of high-frequency spectrum. However, this increased bandwidth comes at the cost of unpredictable scenarios, such as sudden changes in channel conditions due to mobility or obstructions and lengthy delays in long-distance connections. Such fluctuations affect the performance of upper-layer Internet protocols employed by applications such as TCP and QUIC. Questions that need to be answered include the ability to adapt after a drastic change in network conditions and whether the adaptation time is sufficient for applications to take advantage of the high-capacity channel before a new fluctuation occurs. The project aims to design and evaluate a congestion control algorithm capable of efficiently adapting to the fluctuating bandwidth of extreme condition scenarios of 5G-A/6G mobile networks. Thus, after the implementation of 5G-advanced and 6G in mmWave, it will be possible to create advanced services through demanding applications such as Augmented Reality (AR) and Virtual Reality (VR), Remote Surgery, and Telemedicine, Smart Manufacturing, among others., with high performance under these new scenarios.

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Faculty Supervisor:

Sandra Cespedes

Student:

Partner:

Universidad de Chile

Discipline:

Computer science

Sector:

Education

University:

Concordia University

Program:

Globalink Research Award

Numerical modelling of unsaturated frozen soil using OpenGeoSys

The proposed research project addresses the critical issue of the ground responses of frozen soils in cold regions, specifically focusing on the thermo-hydro-mechanical behavior of frozen soils during freeze-thaw actions. During the ground freezing process, the freezing front penetrates progressively downward in soils and frost heave can be generated. Frost heave is a common cause of engineering disasters in cold regions (e.g., pipe rupture and foundation damage). Upon ground thawing, geo-disasters like large ground settlements or landslides may be triggered. Reliable models are needed to quantify the freeze–thaw actions in soils as a porous media containing solid soil particles, ice, liquid water, and air. However, most previous numerical tools have a limited capacity for simulating large-scale problems. The application to a field-scale geo-engineering problem is limited. Thus, the codes are subject to be implemented through a high-performance platform. We propose to collaborate with the hosting supervisor Prof. Thomas Nagel from Technische Universität Bergakademie Freiberg, Germany to implement our previous FEM code through OpenGeoSys. The developed numerical package using OpenGeoSys will be applied to simulate a ground response under ground-source heat pump (GSHP) operations in a permafrost region of Canada.

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Faculty Supervisor:

Biao Li

Student:

Partner:

Technische Universität Bergakademie Freiberg

Discipline:

Engineering

Sector:

Sustainability & the Environment; Green/Alternative Energy; Construction

University:

Concordia University

Program:

Globalink Research Award

Traitement des matériaux de gypse

Ce nouveau stage propose de tester la faisabilité sur le terrain des méthodes expérimentées au laboratoire par la mise en place d’essais pilotes sur les sites d’enfouissement. On testera également la méthode qui consiste à recouvrir les sites d’enfouissement par des matériaux de recouvrement. Cette technique peut s’avérer très efficace du fait qu’elle regroupe l’ensemble des mécanismes physique, chimique et biologique dans la réduction de l’impact des panneaux de gypse sur l’environnement. Ces matériaux peuvent être :
? Le compost de boue riche en fer, les écorces et copeaux de bois : adsorption, minéralisation de la matière organique (Processus Redox).
? Les résidus de béton fin (d<2 mm) ou la chaux, Ca(OH)2, CaCO3 pour leurs propriétés alcalines. ? Le sable : grâce à ses propriétés physiques. ? Un mélange 3:1 de cendre et d’oxyde de fer, l’oxyde de fer : propriété d’oxydation. Les données expérimentales recueillies permettront d’ouvrir la voie sur la possibilité de modéliser les mécanismes liés aux propriétés des panneaux de gypse placés en conditions naturelles des décharges.

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Faculty Supervisor:

Alfred Jaouich

Student:

Partner:

Delsan-AIM Inc

Discipline:

Earth science

Sector:

Administrative and support, waste management and remediation services

University:

Université du Québec à Montréal

Program:

Accelerate

Discovery of potent beta-lactamase inhibitor peptides to overcome beta-lactamase-mediated antibiotic resistance

The emergence and spread of antibiotic resistant bacteria is a major threat to our ability to treat bacterial infections. The beta-lactams, a group that includes the penicillins, are a widely used group of antibiotics. However, bacteria can become resistant to beta-lactams by producing beta-lactamases, enzymes that inactivate these antibiotics. There has been great success in treating infections caused by beta-lactam antibiotics by administering these antibiotics alongside a beta-lactamase inhibitor (BLI). Due to the continuing evolution of resistance, new BLIs are urgently needed. The intern will work in a collaborative research environment to test and apply a new biosensor-based screening platform for BLI discovery developed in the lab of the host supervisor. Peptides derived from natural beta-lactamase inhibitor proteins will be screened and optimized, testing for activity against a panel of beta-lactamases. Hits will be validated against clinical strains of beta-lactamase-producing bacteria to test their efficacy. This strategy could yield new BLIs that can rescue the use of beta-lactam antibiotics as therapeutics. Furthermore, this project will promote further collaboration between the labs of the host and home supervisors towards the development of other new BLIs.

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Faculty Supervisor:

Christopher Lohans

Student:

Partner:

University of Oxford

Discipline:

Life Sciences

Sector:

Pharmaceuticals

University:

Queen's University

Program:

Globalink Research Award

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