Innovative Projects Realized

Design, synthesis and charaterization of new p-AQM macromolecules for electronics applications

This project focuses on synthesizing a new class of conjugated polymers incorporating stable, quinoidal units that enhance electronic properties, targeting applications in organic field-effect transistors (OFETs), organic solar cells, and organic electrochemical transistors (OECTs). By designing polymers that feature reduced bond-length alternation, these materials exhibit lower band gaps and high charge carrier mobilities, essential for efficient energy and electronic applications. Using a green synthesis route, we avoid organometallic reagents and catalysts, opting instead for sustainable methods that lock the polymer backbone in a rigid conformation. This structural control enhances orbital delocalization and interchain coupling, boosting charge transport efficiency. The project will benefit both institutions by advancing sustainable, high-performance materials that bridge the gap between environmental responsibility and cutting-edge electronic functionality, supporting developments in bioelectronics, flexible electronics, and eco-friendly device manufacturing.

Development of electrospun PMMA/PEG/Sio2 polymer nano-composites for Carbon Capture

The proposed project fosters collaboration between Sabanci University and the University of Waterloo, offering significant benefits to both institutions. Sabanci University will gain access to advanced imaging and gas analysis techniques available at Waterloo, enabling precise characterization and optimization of the CO2 capture system. This enhances the quality and impact of ongoing research at Sabanci. Meanwhile, the University of Waterloo will benefit from participating in cutting-edge research that aligns with global climate action goals, advancing its expertise in sustainable CO2 capture technologies. The partnership strengthens both institutions’ research profiles, promotes knowledge exchange, and paves the way for future collaborations in innovative environmental solutions.

Jumine : Anomalies en flottation minière : amélioration et optimisation du système de détection existant

Le projet vise à améliorer un système de détection des anomalies dans des cellules de flottation, un procédé employé dans l’industrie minière. Actuellement, un détecteur d’anomalie développé par Jumine dans la cellule de flottation identifie des problèmes tels que la vitesse inappropriée de la mousse, son affaissement ou encore sa coalescence trop importante, mais ne fournit pas d’explications ni de solutions.
Le projet vise à expliquer et résoudre ces anomalies en analysant conjointement a) les données des capteurs dans la cellule de flottation et b) les images en continu de la mousse à la surface des cellules de flottation. Le stagiaire sera chargé de développer un modèle utilisant l’apprentissage automatique (AA) non supervisé pour détecter les différents types d’anomalies (labels faibles). Ces données faiblement étiquetées seront ensuite validées par un humain qui examinera les images correspondantes. Ce nouvel ensemble de données étiquetées permettra d’entraîner un classificateur capable d’identifier chaque classe d’intérêt.
Les méthodes d’explicabilité en AA fourniront des explications détaillées sur les anomalies détectées, permettant aux opérateurs de prendre des mesures correctives plus informées, améliorant ainsi l’efficacité du processus de concentration des minéraux.

MOREAU_MÉRAND_Barcelone

This project will examine how the positions of central governments influence the diplomatic strategies of regional entities, such as Catalonia and Scotland, during sovereignty referendums. It focuses on protodiplomacy, which refers to the diplomatic efforts of subnational regions seeking international recognition for their independence movements. The main goal is to conduct interviews with key people involved in the independence movements, such as local politicians and diplomats, to understand the strategies these regions use to gain support and recognition from other countries. The project will also involve organizing workshops to share knowledge between academics and local experts, helping to build a network of researchers focused on this topic. The expected benefits of this research include a better understanding of how regions influence international opinions and gain support during referendums, as well as contributing new insights into the theory of paradiplomacy and the challenges regions face when they seek to be recognized internationally.

Métallooligomères à base de porphyrines et de diketopyrrolopyrroles pour des applications de cellules solaires

Ce projet vise à fabriquer deux nouveaux polymères qui offrent des propriétés supérieures en vue de construire des cellules solaires plastiques. Ces propriétés consistent d’un meilleur empilement et d’une meilleure géométrie planaire pour améliorer le transport des charges, et de composantes judicieusement choisies pour améliorer la vitesse du photo-transfert du premier électron afin de minimiser les pertes d’énergie lumineuse en chaleur. Ces composantes seront des porphyrines (comme l’on retrouve dans hémoglobine) et du dicétopyrrolopyrrole (un pigment), des ponts thiophène et thiazole. Finalement après caractérisation, des cellules solaires seront fabriquées et testées.

Development of a sub-unit vaccine to protect swine against the infections caused by Streptococcus suis

Streptococcus suis is one of the most important causes of bacterial disease in post-weaned piglets. Affected animals suffer from meningitis (affected brain), endocarditis (affected heart), arthritis (affected joints) and septicemia (general infection). There are 35 serotypes of S. suis (same bacteria but different antigens). Some of these serotypes (such as serotype 2) can also affect humans (transmission from pigs), causing serious disease. Usually, veterinarians use antibiotics to treat and even protect animals. However, the large use of antibiotic induces the increase of antibiotic-resistance and there are now many S. suis bacterial strains that are resistant. Unfortunately, there are no effective vaccines in the market to protect against this infection. We have identified a protein called “Sao” that protects pigs against a bacterial strain of S. suis serotype 2. It is not known if it protects against other strains and other serotypes that cause disease in pigs. Production of Sao protein should also be improved to obtain acceptable yields to have enough material to be tested in a large vaccine trial. In addition, this protein should be mixed with a very good adjuvant that increases or aids the immune response of animals and used in pigs.

Détection précoce des épisodes d’hypoglycémie par intelligence artificielle : une approche personnalisée intégrant des mécanismes d’attention

Le diabète de type 1 expose les patients à des épisodes d’hypoglycémie, des baisses dangereuses du taux de sucre dans le sang, qui peuvent entraîner des symptômes graves tels que des vertiges, des évanouissements, voire des convulsions ou un coma. Une détection précoce de ces épisodes est essentielle pour permettre aux patients de réagir rapidement et ainsi éviter des complications potentiellement graves.

Ce projet propose de développer un système de détection intelligent basé sur l’intelligence artificielle (IA). En utilisant les données issues des dispositifs de mesure continue du glucose (CGM) et des algorithmes d’apprentissage profond, nous cherchons à créer une solution capable de prédire les épisodes d’hypoglycémie avant qu’ils ne deviennent critiques. Cette approche personnalisée permettra de fournir des alertes précises et adaptées à chaque patient, réduisant ainsi les faux positifs et améliorant la gestion quotidienne de la glycémie.

Cette technologie a pour objectif d’améliorer la qualité de vie des patients atteints de diabète en leur offrant des outils fiables et proactifs pour gérer leur santé tout en contribuant à l’avancement de la recherche dans le domaine de la santé numérique.

Application Testing and Marketing Strategy for a Travel App – BC-923

The project aims to enhance the user experience (UX) of Pax Travel’s innovative travel app, designed to transform travel influencers’ videos into bookable itineraries. This initiative will include comprehensive UX testing to identify and resolve design and usability challenges, ensuring a seamless and user-friendly interface. Additionally, the project will involve creating sample travel videos to enrich the app’s content, providing users with a more engaging experience. These enhancements are expected to optimize app functionality, attract a broader audience, and boost user engagement, thereby supporting Pax Travel in achieving a successful launch and securing a competitive edge in the travel sector.

Efficient Distributed Learning for Autonomous Multi-Reconfigurable Intelligent Surfaces Operation

The sixth-generation (6G) wireless communication networks promise transformative advancements in various sectors by enhancing speed, reliability, and connectivity to support applications like autonomous vehicles, smart healthcare, immersive augmented reality (AR), and the Internet of Everything (IoE). Integrated sensing and communication (ISAC) technologies are pivotal in 6G, enabling advanced applications through intelligent metasurfaces. The deployment of AI and machine learning (ML) within 6G networks is essential for managing complex network tasks, enhancing security, and optimizing performance. These technological advancements collectively contribute to the realization of intelligent, context-aware, and user-centric applications across various domains, heralding a new era of connectivity and smart services.
Integrating and operating passive RIS into 6G communication networks presents several challenges, particularly in the search space for optimizing RIS-aided communication networks. We therefore seek to design an efficient distributed learning approach over a novel hybrid RIS architecture with energy-efficient sensing capabilities. This work builds upon the previous MITACS Accelerate project # IT29537 where a passive RIS prototype operating at 3.75GHz (n77 and n78 TDD 5G frequency band) has been developed and integrated to the 5G Open radio access network.

A Technology Management Analysis Platform

the context of emerging technologies, this project aims to develop a practical management tool that can help technology firms to fully assess new technology value proposition, formulate the risks & opportunities profile, and develop implementation plan.

Enhancing User Interaction in VR Striking Sport Games through Haptic Feedback and Visual Immersion

Our project addresses challenges in VR striking sports games, where the lack of accurate physical feedback limits VR’s ability to promote physical activity. Building on an existing NAIST project, we propose to enhance their haptic device into a sport-universal tool that improves realism and immersion by replicating real-world sports interactions (e.g., striking a ball) across various VR striking sports games. We will refine the device, develop software for user experiments, and employ iterative design processes to optimize performance. By the end, we plan to have a fully developed haptic device and user study. This study will determine the best approach to enhance realism and immersion in VR striking sports games and evaluate our device’s potential as a universal tool for multiple sports. The student will work at NAIST CARE Lab under Prof. Kiyokawa’s supervision, gaining access to cutting-edge equipment and mentorship from leading haptic experts. This opportunity will deepen their knowledge of haptics, foster international collaborations, provide professional growth, and prepare them for pursuing a PhD in haptics. This experience also benefits both institutions. The partnership strengthens research ties, encouraging the exchange of knowledge, expertise, and resources. It also drives joint innovations, establishing their reputations and contributions in research communities.

Developing ROV-based Workflows for Coastal Monitoring in a Changing Climate

In many parts of the Great Lakes, including southeastern Lake Huron, coastal bluffs are eroding. This poses a significant threat to homes, infrastructure, and the region’s tourism industry. To reduce damage to infrastructure, local conservation authorities create development setbacks to try to prevent new structures from being built in harms way. However, these setbacks are based on historical patterns of bluff retreat, which may not persist in our changing climate due to lower lake ice cover, more frequent storms, and changing water level cycles in the Great Lakes. This project aims to develop a “toolkit” within ArcGIS Pro to assist coastal managers in collecting, analyzing, and doing modelling with coastal data. This will allow coastal researchers to generate process-based predictions of how quickly the bluffs may retreat in the future under a variety of climate change scenarios.