Projets novateurs réalisés

UnACoRN: Understanding Affirming Communities, Relationships, and Networks

In recent years, numerous jurisdictions in the USA and Canada have enacted bans on ‘conversion’ practices, i.e., organized attempts to suppress Two-Spirit, lesbian, gay, bisexual, transgender, queer (2S/LGBTQ+), and other minoritized sexual and gender identities. In 2022, our team conducted the UnACoRN survey, a first-of-its-kind binational survey of 9,679 youth (15-29 years of age). Through this project, we are beginning to appreciate the full range of settings and practices that threaten 2S/LGBTQ+ identities, despite ‘conversion’ practice bans and other policy advances to protect the rights of 2S/LGBTQ+ people. Leveraging collaborations between SFU, Vanderbilt, and other North American institutions, we will analyze and disseminate findings in 2022-23, aiming to support 2S/LGBTQ+ health equity strategies. Results will also be used to inform more inclusive and comprehensive approaches to sex education, organized team sports, and places of faith. Finally, UnACoRN data will shed light on where and how we can use the federal ban to educate parents/caregivers, youth, and those in authority to understand the harms of anti-2S/LGBTQ+ messages and contribute to health equity for 2S/LGBTQ+ populations.

Novel cellulose-based membranes for CO2 filtration and ion exchange in aluminum/air batteries

Climate change due to CO2 emission as a result of burning fossil fuels has become an urgent environmental
concern. Moving towards developing clean and sustainable energy sources is inevitable. Expansion of
electrification in the energy sector is one of the effective approaches to developing cleaner and more sustainable
energy sources. Metal-air batteries that are assembled from a metal anode and an air-breathing cathode in a
proper electrolyte, are very promising candidates for clean energy substitutes. AlumaPower is one of the leading
companies in the commercialization of metal-air batteries in Canada. To meet the prerequisites of
commercialization, nevertheless, there are still many technical challenges that need to be addressed. Our
proposal is seeking key solutions that will lead AlumaPower to its goal and has planned an innovative and
comprehensive research project for implementing them. Our solutions are mainly based on developing and
optimizing the performance of advanced functional materials to improve the energy density and service life of
metal-air batteries. Developing such materials will help AlumaPower to consolidate Canada’s role as an important
player in the clean-energy industry.

Building Spatio-temporal Transformers for Egocentric 3D Pose Estimation

Using a fisheye head-mounted camera to estimate human pose in 3D has become increasingly popular in recent years due to its ability to capture activities in unconstrained environments. Egocentric 3D human pose estimation (HPE) has a number of challenges due to self-occlusions and strong distortions. Intermediate heatmap-based representations have been found to be effective in reducing distortion, however self-occlusion remains a challenge, and is the proposed focus of this internship. The goal of the project is to build on previous work, the Ego-STAN project, to improve the performance of that method in the context of 3D HPE, particularly to make it more robust to occlusion. The broader goal is to have a method suitable for cutting-edge motion tracking applications such as activity recognition, surgical training, and immersive XR applications.

Business interns within cross-functional teams to develop and commercialize AI-powered solutions – Part 2

AltaML is an innovative company capitalizing on a major technological trend: artificial intelligence (AI) technologies, enabled by big data, are driving a fourth industrial revolution. AI will transform all industries, but traditional industries face challenges in implementing AI. AltaML has a unique business model to overcome barriers to adoption of AI solutions by industry, which is to bring the innovating startup together with the large organization, thereby bringing together rich datasets, AI talent with a playbook for industry application and the close collaboration of subject matter experts and AI experts–with a mindset for change. In addition to AI expertise, we bring agility that our large, corporate partners often lack, and which is so essential for innovation. With a strategic focus on AI adoption and product, AltaML works across industries as well as with the public sector using a co-development approach to create applied AI solutions as well as joint AI ventures. This rich, complex multisectoral environment provides the breadth that enables insights in one area to be applied in new areas, leading to ever increasing opportunities for innovation.

The project comprises internships in a variety of technical and business roles, which are: associate machine learning developer, business development associate, communications associate, finance associate, associate business solutions consultant, and project delivery associate. Outcomes will include algorithm creation and deployment, data visualizations, market research reports, sales collateral, competitive landscape analysis, feasibility analysis; key messages and content writing such as case studies and feature articles, financial model development, data analysis, financial reports and variance analysis, customer workflow mapping, business case reports, resource allocation plans, project update reports, and project plans.

Plannification des horaires des agents enfonction des prévisions des arrivées d’appelsdans les centres d’appels d’Hydro-Québec

La gestion des opérations de centre d’appels d’Hydro-Québec est une tâche très complexe qui implique souvent un équilibre entre des objectifs contradictoires. En effet, les gestionnaires ont pour but d’atteindre des niveaux élevés à la fois en termes de qualité de service et d’efficacité opérationnelle. La qualité du service est généralement mesurée par les principaux indicateurs de performance cibles tels que le temps moyen d’attente des appelants. L’efficacité opérationnelle est généralement mesurée par la proportion de temps durant laquelle les agents sont occupés à traiter les appels. On peut facilement voir que des niveaux élevés de qualité de service sont associés à de faibles niveaux d’efficacité opérationnelle, et vice versa. Le but de ce projet est d’offrir une aide logicielle aux gestionnaires de centres d’appel lors de la conception des emploi du temps des agents, et ceci en fonction de prévisions à long terme de la demande future entrante (ie, les volumes d’appels futurs)

Machine learning developer interns within cross-functional teams to develop and commercialize AI-powered solutions – Part 3

AltaML is an innovative company capitalizing on a major technological trend: artificial intelligence (AI) technologies, enabled by big data, are driving a fourth industrial revolution. AI will transform all industries, but traditional industries face challenges in implementing AI. AltaML has a unique business model to overcome barriers to adoption of AI solutions by industry, which is to bring the innovating startup together with the large organization, thereby bringing together rich datasets, AI talent with a playbook for industry application and the close collaboration of subject matter experts and AI experts–with a mindset for change. In addition to AI expertise, we bring agility that our large, corporate partners often lack, and which is so essential for innovation. With a strategic focus on AI adoption and product, AltaML works across industries as well as with the public sector using a co-development approach to create applied AI solutions as well as joint AI ventures. This rich, complex multisectoral environment provides the breadth that enables insights in one area to be applied in new areas, leading to ever increasing opportunities for innovation.

The project comprises internships in a variety of technical and business roles, which are: associate machine learning developer, business development associate, communications associate, finance associate, associate business solutions consultant, and project delivery associate. Outcomes will include algorithm creation and deployment, data visualizations, market research reports, sales collateral, competitive landscape analysis, feasibility analysis; key messages and content writing such as case studies and feature articles, financial model development, data analysis, financial reports and variance analysis, customer workflow mapping, business case reports, resource allocation plans, project update reports, and project plans.

Machine learning developer interns within cross-functional teams to develop and commercialize AI-powered solutions – Part 2

AltaML is an innovative company capitalizing on a major technological trend: artificial intelligence (AI) technologies, enabled by big data, are driving a fourth industrial revolution. AI will transform all industries, but traditional industries face challenges in implementing AI. AltaML has a unique business model to overcome barriers to adoption of AI solutions by industry, which is to bring the innovating startup together with the large organization, thereby bringing together rich datasets, AI talent with a playbook for industry application and the close collaboration of subject matter experts and AI experts–with a mindset for change. In addition to AI expertise, we bring agility that our large, corporate partners often lack, and which is so essential for innovation. With a strategic focus on AI adoption and product, AltaML works across industries as well as with the public sector using a co-development approach to create applied AI solutions as well as joint AI ventures. This rich, complex multisectoral environment provides the breadth that enables insights in one area to be applied in new areas, leading to ever increasing opportunities for innovation.

The project comprises internships in a variety of technical and business roles, which are: associate machine learning developer, business development associate, communications associate, finance associate, associate business solutions consultant, and project delivery associate. Outcomes will include algorithm creation and deployment, data visualizations, market research reports, sales collateral, competitive landscape analysis, feasibility analysis; key messages and content writing such as case studies and feature articles, financial model development, data analysis, financial reports and variance analysis, customer workflow mapping, business case reports, resource allocation plans, project update reports, and project plans.

Machine learning developer interns within cross-functional teams to develop and commercialize AI-powered solutions – Part 1

AltaML is an innovative company capitalizing on a major technological trend: artificial intelligence (AI) technologies, enabled by big data, are driving a fourth industrial revolution. AI will transform all industries, but traditional industries face challenges in implementing AI. AltaML has a unique business model to overcome barriers to adoption of AI solutions by industry, which is to bring the innovating startup together with the large organization, thereby bringing together rich datasets, AI talent with a playbook for industry application and the close collaboration of subject matter experts and AI experts–with a mindset for change. In addition to AI expertise, we bring agility that our large, corporate partners often lack, and which is so essential for innovation. With a strategic focus on AI adoption and product, AltaML works across industries as well as with the public sector using a co-development approach to create applied AI solutions as well as joint AI ventures. This rich, complex multisectoral environment provides the breadth that enables insights in one area to be applied in new areas, leading to ever increasing opportunities for innovation.

The project comprises internships in a variety of technical and business roles, which are: associate machine learning developer, business development associate, communications associate, finance associate, associate business solutions consultant, and project delivery associate. Outcomes will include algorithm creation and deployment, data visualizations, market research reports, sales collateral, competitive landscape analysis, feasibility analysis; key messages and content writing such as case studies and feature articles, financial model development, data analysis, financial reports and variance analysis, customer workflow mapping, business case reports, resource allocation plans, project update reports, and project plans.

Business interns within cross-functional teams to develop and commercialize AI-powered solutions – Part 1

AltaML is an innovative company capitalizing on a major technological trend: artificial intelligence (AI) technologies, enabled by big data, are driving a fourth industrial revolution. AI will transform all industries, but traditional industries face challenges in implementing AI. AltaML has a unique business model to overcome barriers to adoption of AI solutions by industry, which is to bring the innovating startup together with the large organization, thereby bringing together rich datasets, AI talent with a playbook for industry application and the close collaboration of subject matter experts and AI experts–with a mindset for change. In addition to AI expertise, we bring agility that our large, corporate partners often lack, and which is so essential for innovation. With a strategic focus on AI adoption and product, AltaML works across industries as well as with the public sector using a co-development approach to create applied AI solutions as well as joint AI ventures. This rich, complex multisectoral environment provides the breadth that enables insights in one area to be applied in new areas, leading to ever increasing opportunities for innovation.

The project comprises internships in a variety of technical and business roles, which are: associate machine learning developer, business development associate, communications associate, finance associate, associate business solutions consultant, and project delivery associate. Outcomes will include algorithm creation and deployment, data visualizations, market research reports, sales collateral, competitive landscape analysis, feasibility analysis; key messages and content writing such as case studies and feature articles, financial model development, data analysis, financial reports and variance analysis, customer workflow mapping, business case reports, resource allocation plans, project update reports, and project plans.

Novel fuel cell materials and designs for high performance

Polymer electrolyte membrane fuel cells are a promising solution to addressing climate change, as they can produce emission free energy on demand using hydrogen as fuel. Despite their benefits, many challenges remain in the way of widespread commercialization of these devices. Specifically, components such as the gas diffusion layer (GDL) and catalyst coated membrane (CCM) suffer from poor mass transport and durability issues. These components must be designed for durability and improved transport properties to become commercially viable. To address these challenges, we propose to apply both pore network modelling and advanced electrochemical characterization techniques to reveal the mechanisms responsible for degradation in the performance of the GDL and CCM. The insights gained from this collaborative work with Prof. Auvity will inform the design of next-generation fuel cell porous media for clean energy applications.

Post-discharge health-related quality of life, disability, and risk of post-traumatic stress disorder amongst the survivors of the veno-venous extracorporeal membrane oxygenation during the COVID-19 pandemic

During the COVID-19 pandemic, patients with severe pneumonia sometimes required a type of life-support
machine for their lungs called ECMO. Using large intra-venous lines, ECMO removes blood from a patient, adds
oxygen to the blood, and puts it back into the body. While it can be life-saving, some patients can develop a
brain injury while on ECMO. However, the long-term effects on the brain of being on an ECMO machine are not
known. Some patients may experience difficulties with high-level thinking, or emotional difficulties like
depression or post-traumatic stress disorder. The purpose of this study is to examine cognitive and emotional
function of patients who have survived ECMO. We will contact patients after they have been discharged home
and ask them to complete tests of cognitive and emotional function. We can then use this information to see
which patients may be at risk of developing these issues, so we can better support them in the future.

A framework to enhance deep learning systems’ trustworthiness against Out of Distribution examples

In the past decade, deep learning models have demonstrated their highest performance for a variety of tasks. These models outperformed classical machine learning models and even humans in terms of performance and accuracy. However, previous research indicated that these models are vulnerable to out-of-distribution and adversarial inputs. Ideally, these inputs should be rejected by the deep learning model, but the deep learning model generates confident outcomes for it. In this research, we develop a framework that assesses the deep learning model’s vulnerabilities against such inputs, detects and rejects these malicious input , and enhances deep learning models to generate less confident labels for them.