Past IRD Recipients
2024 Exploratory | ED PreVisit: A Multilingual AI Solution for Pre-ED Visit Consultation, Enhanced Demand Forecasting, and Improved Patient Experience in Emergency Departments
Overview: The "ED PreVisit" web application is an innovative AI-driven tool designed for patients planning a visit to an Emergency Department (ED), allowing them to undergo a preliminary self-triage prior to their physical arrival. With data sourced from renowned hospitals such as Jewish General Hospital, the application identifies symptom patterns, anticipates potential outcomes, and tailors its questioning to pinpoint the patient's chief complaint. With a user-friendly bilingual interface, patients input vital details and describe symptoms, while the app transforms this data into the IT system of the target ED. This proactive approach not only expedites the registration and triage process, but also avoid unnecessary ED visits by directing non-urgent patients to general practitioners or pharmacists. Moreover, it provides ED managers with future information about patient arrivals, which can be used for better demand forecasting and resource planning. This app can also offer estimated waiting times for various EDs, allowing patients to choose one with the shortest wait. Once a patient selects an ED and submits the questionnaire, the app will also provide tailored preparation instructions for the ED visit, based on the patient’s profile and chief complaint. Spanning from January 1 2025 to December 31, 2025, the project's focus is the development and internal evaluation of the app, ensuring its efficacy and ease of use.
Core Team
Yichuan Ding
Associate Professor of Healthcare Analytics, Desautels Faculty of Management
Steve Liu
Professor of Electrical and Computer Engineering, Associate Member of MILA, Fellow of the Canadian Academy of Engineering and Fellow of the IEEE
Lawrence Rosenberg
Professor of Surgery and Medicine, President & CEO of CIUSSS Central West
Li Jiang
PhD student, Operations Management, Desautels Faculty of Management
Erin Cook
Director of Quality, Transformation, Evaluation, Value, Ethics, and Virtual Care, CIUSSS Centre-Ouest-de-l'Île-de-Montréal
Jennifer Gutberg
Embedded Scientist of Quality, Transformation, Evaluation, Value, Clinical & Organizational Ethics, and Virtual Care, CIUSSS Central West
2024 Exploratory | How can generative AI be used to optimize content creation for secondary math use?
Overview: As students enter high school, math topics tend to become more abstract, which proves difficult for many students and requires additional instructional support. Teachers of advanced mathematics need more resources to support their students' learning, but their options are currently limited. Even with the growth of online resources, many do not provide personalized support or are not connected to specific secondary math curricula. Some teachers are starting to turn to generative AI to help create new content, but little is known about how they should do so. Specifically, generative AI (genAI), such as ChatGPT, has not typically been created for educational purposes and given that many are based large language models (LLMs), there is a growing need to understand how these tools can be used to optimize teaching and learning in mathematics. In this project, we will use an interdisciplinary approach to explore three main areas: 1) Why and how teachers are (or are not) using generative AI, 2) Teachers needs with regard to content/resource generation, and 3) The scope of existing genAI tools.
Core Team
Nikki Lobczowski
Assistant Professor, Faculty of Education, Learning Science Program
Siva Reddy
Assistant Professor, School of Computer Science & Department of Linguistics
MILA Quebec
MQ Wu
PhD student, Faculty of Education, Learning Science Program
Arkil Patel
PhD student, School of Computer Science
MILA Quebec
Shuai Chen
PhD student, Faculty of Education, Learning Science Program
Alex Krantz
Undergraduate student, Computer Science and Mathematics
Michael Yu
Undergraduate student, Computer Science
2024 Exploratory | AI-Powered Aerial-Ground Collaborative Mobile System for Precision Spraying to Enhance Sustainable Agriculture
Overview: Remarkable increases in the use of synthetic herbicides have been reported for weed control. However, up to 98% of crop spray does not stay on the plants and flows into the environment, causing soil and water pollution. Therefore, reducing herbicide use is critically needed to develop resilient and sustainable agriculture, and it has significant positive impacts on public health, society, and the ecological environment. In this initiative, we aim to develop an AI-powered aerial-ground collaborative mobile system for precision spraying to reduce herbicide use.
Core Team
Shangpeng Sun
Assistant Professor, Department of Bioresource Engineering
François Grondin
Assistant Professor, Electrical and Computer Engineering, Université de Sherbrooke
Philippe Seguin
Professor, Plant Science
2024 Proof of Concept | Inclusive co-design of AI systems
Overview: When AI systems are adopted in critical applications, any failure can pose serious risks to the health, safety, and well-being of users or other related stakeholders. Accurate estimation of the severity of the risks and thorough planning for mitigating them are indispensable but extremely challenging. This is especially true for marginalized and minority communities. Considering such a gap, we aim to accelerate the design of inclusive AI systems through a concrete case study of an accessible form of payment for the elderly population. As a first step, we plan to identify the barriers preventing marginalized users, in particular the elderly population, from participating in the design process of such AI systems. The outcomes from this research contribute to improving the existing co-design practices toward the development of inclusive AI, and inform the construction of a shared set of vocabulary that technologists and policymakers can use to prevent harms and risks AI can bring to the minority and marginalized stakeholders of the technology at design time.
Core Team
Jin Guo
Associate Professor, School of Computer Science
AJung Moon
Assistant Professor, Electrical and Computer Engineering
Karyn Moffatt
Associate Professor, School of Information Studies
Canada Research Chair in Inclusive Social Computing
Jutta Treviranus
Professor, Faculty of Design, Ontario College of Art & Design (OCAD)
Director of the Inclusive Design Research Centre (IDRC)
2024 Proof of Concept | Using AI to support Culturally Grounded Indigenous Education
Overview: Research has shown that culturally grounded education for Indigenous community members supports engagement, wellbeing, and learning. However, implementing culturally grounded education effectively, particularly in remote areas, has proven difficult due to the lack of culturally grounded materials and the time it takes to create quality curriculum. Over the past 6 years our team has been able to develop and implement culturally grounded curriculum in rural Indigenous areas of Peru. However, it is a challenge to do this work at scale. Artificial intelligence (AI) shows promise for addressing this issue. To demonstrate that AI can create culturally grounded learning materials and curriculum based in community epistemologies, our team will train offline AI software to use community-led, collaboratively gathered knowledge, such as local plants, animals, and cultural practices to foster literary, numeracy, and critical thinking skills based in communities’ ways of thinking and being. This work will engage in community-based practices and follow First Nations OCAP ethical principles.
Core Team
Joseph Levitan
Associate Professor, Department of Integrated Studies in Education
Catherine Potvin
Professor, Department of Biology
Trottier Fellow from the Trottier Institute for Science and Public Policy
Director, PFSS: Panama Field Study Semester. Canada Research Chair in Climate Change Mitigation and Tropical Forest (Tier 1)
Bryan Leung
Associate Professor, Department of Biology
UNESCO Chair for Dialogues on Sustainability
Director of the McGill STRI, Neotropical Environment Option
Carmen Moritz
PhD student, Anthropology
Homilia Flaco
Teacher from the Emberá Nation
Oliver Chamorro
Computer technician from the Emberá Nation
Juanico Ortega
Emberá knowledge holder
Daniel Zuniga
Peruvian collaborator
