Innovative Projects Realized

The Manitoba Non-Profit Housing Association (MNPHA)

The main goal of this project is to create a practical Safety Toolkit for non-profit housing providers in Manitoba. The toolkit will help them address safety challenges in their buildings, including issues like tenant conflicts, break-ins, drug activity, and supporting vulnerable tenants. Both interns, Judith and Olu, will work together on all parts of the project, but will divide tasks as needed —such as splitting research, drafting toolkit sections, and conducting interviews— so the project moves efficiently. This will ensure the final toolkit is realistic, easy to use, and ready to help housing providers improve safety in their communities.

Food and neighbourhood well being

This project involves a four-month internship where I will help lead the daily coordination of the West Broadway Farmers’ Market and help manage the Good Food Club’s summer field trip program. As an Education student, I will use my academic training to design and run community workshops that make information about food and nutrition easy for everyone to understand. The West Broadway Community Organization will benefit by having a dedicated lead to oversee volunteer teams and improve their market operations through new, professional manuals and evaluation reports. Ultimately, this work helps the organization run more smoothly and strengthens their ability to provide high-quality, inclusive programming for the neighborhood.

Développement et évaluation d’une application de soutien par les pairs en milieu étudiant (SafeSpace)

De nombreuses personnes vivent des difficultés liées à leur santé mentale sans avoir accès rapidement à du soutien. SafeSpace est une application mobile qui offre des groupes de soutien en ligne, animés par des personnes formées, dans un cadre sécuritaire, anonyme et non clinique. Ce projet de recherche vise à mieux comprendre comment ces groupes de soutien numériques peuvent contribuer à la santé globale et au bien-être des personnes qui y participent. En étudiant l’expérience réelle des utilisateurs, la recherche permettra d’identifier ce qui fonctionne le mieux et pourquoi. Les résultats aideront à améliorer la plateforme SafeSpace et à développer des solutions de prévention accessibles, humaines et adaptées aux besoins actuels. Ce projet contribuera également à mieux outiller les organisations qui souhaitent offrir du soutien psychosocial complémentaire aux services existants

Enhancing Public Access to Canadian Arms Export Data

This project will develop an open-source tool to improve access to information about Canadian defence exports and support a clearer understanding of Canada’s role in the global arms trade. Currently, data on Canadian defence exports is spread across multiple sources and can be difficult to verify or analyze. The project will create an automated system that collects and validates export data, helping produce more accurate and timely estimates of Canada’s annual defence trade. By making this information easier to access and analyze, the project will help researchers, policymakers, journalists, and the public better understand patterns and trends in Canadian defence exports. For the partner organization, Project Ploughshares, the system will strengthen its ability to track and analyze arms transfers, support research and reporting, and contribute reliable data to discussions about Canada’s defence industry and export policies.

Short Hive Audio Recording Predictor

Over the past decade, researchers and practitioners have explored the potential of audio recording for precision beekeeping. Most of the research focused on in – hive sensors and real – time detection of critical events, such as swarming, queen state or hive strength. However, adoption of such sensors is difficult in a low margin industry such as beekeeping. On the other hand, most, if not all, beekeepers have a smartphone. As such, in this work we explore the potential of using short audio segments recorded from beehives. Such non – invasive assessment has been gaining interest mainly to allow beekeepers to lower the number of interventions they make on a hive.

The project aims to extend the model output and optimize its performance. It will developing a Federated learning logic. Many AI systems leverage scale to reach performance, leading to huge energy consumption to accomplish their jobs. At Nectar, we promote a sustainable farming system and building such a system would be counterproductive. Additionally, there is a variation in how beekeepers report strength, mite level and queen status. By personalizing the model on device, we can better personalize the predictions to match the user behavior. Finally, our users often work remotely with low internet connections and our system needs to work offline, therefore making the inference on the device is core to our system.

Developing and deploying such a tool could truly change the paradigm of beekeeping. Indeed, the main driver of mortality is the lack of proper management of varroa destructors, the main pest in beekeeping. By allowing users to not only disrupt the bees in general but also sample quickly and often the mite level, we can promote a true IPM program and solve the biggest challenge of beekeeping, managing mites ! Honeybee pollinate 33% of the food we eat, and the average mortality rate of the last 3 years in the US is over 50% putting our food system at risk and by nature putting our society at risk.

Westrich Pacific – Optimizing Development, Construction, and Leasing Workflows for Organizational Growth

This project will help Westrich Pacific strengthen the internal systems that support its high-rise development, construction, and leasing operations as the company continues to grow across Western Canada. The proposal notes that Westrich faces increasing complexity in areas such as “internal communication between development, construction, and leasing teams” and “workflow standardization across projects and regions.” The intern will map current workflows, identify bottlenecks, benchmark industry best practices, and develop improved procedures and reporting tools—including a prototype dashboard for tracking construction and leasing performance. These improvements will support more efficient project delivery, better cross-team coordination, and a stronger foundation for scalable growth in the residential development sector.

Ab Initio Nuclear Theory for Neutrinoless Double-beta Decay

Perhaps the most complicated quantum systems in the universe, the many facets of atomic nuclei are intertwined with some of the most profound questions in nature. The aim of nuclear structure theory is to develop a unified first-principles, or ab initio, picture for all atomic nuclei starting from only the fundamental forces at work. This problem is particularly daunting, as we must first construct these forces consistent with the underlying symmetries of strong and electroweak interactions. Then we must develop methods to solve the nuclear many-body problem in a controlled and systematically improvable manner. At the same time we will incorporate advanced machine-learning and AI algorithms for rigorous uncertainty quantification.

In this project, we will attack one of the most critical questions in beyond-standard-model physics involving nuclei: the nuclear matrix element (NME) for neutrinoless double-beta decay, and its connection to new theories of physics beyond the so-called Standard Model, which is crucial to extract the absolute neutrino mass from a hypothetical discovery and guide strategic planning for next-generation searches in Canada and worldwide. All results will directly impact the hundreds of millions of dollars of Canadian investment into all such experimental efforts at TRIUMF and SNOLAB.

Advancing AI Innovation Through Cross-Functional Collaboration (2)

Daman will work alongside the Public Sector Team as an Associate Software Developer.
Unlike traditional single-project placements, Daman will operate as part of a cross-functional technical cohort supporting a diverse portfolio of Government of Alberta initiatives. This flexible model allows the team to deploy the interns across multiple high-priority use cases, such as document classification, workforce optimization, or policy research, depending on immediate operational needs and the stage of the project lifecycle.
The innovation challenge centers on integrating three core technical pillars into public service workflows:
? Agentic AI: Developing autonomous workflows to handle complex decision-support tasks.
? Retrieval-Augmented Generation (RAG): Implementing intelligent search and interaction layers for large-scale government policy repositories.
? Classical Machine Learning: Building predictive models for forecasting staffing demands or service utilization.
Government of Alberta Initiatives include:
1. Wildfire Workforce Optimization: Interns will develop predictive models and agentic agents to optimize Duty Officer assignments. The goal is to reduce burnout risk and overtime costs through better decision support for wildfire leadership.
2. Research Assistant SWAT Team: Supporting the rollout of a production-ready AI product, the interns will join a dedicated team to streamline the deployment of RAG-based search and interaction layers across various GoA partners to accelerate program delivery.
3. Income Support Program Integrity: The cohort will deploy document intelligence and risk-scoring models to handle high application volumes. This initiative uses AI to rapidly flag potential fraud while fast-tracking low-risk applications to shorten decision timelines for vulnerable residents.
The anticipated economic and social benefits include significant cost savings through reduced manual administrative burdens and improved accuracy in resource planning. By modernizing information management and decision workflows, this project directly enhances the efficiency, transparency, and scalability of essential public services provided to Albertans.
Samara will work alongside the Public Sector Team as an Associate Business Solutions Consultant.
Project Description: Alberta’s Income Support program faces growing pressure as high application volumes and manual fraud reviews slow access to critical financial assistance for vulnerable residents. AltaML will partner with the GoA to deploy AI-enabled document intelligence and risk-scoring approaches, drawing on existing solution patterns to rapidly flag potential fraud while fast-tracking low-risk applications. The overall goal is to shorten decision timelines, improve program integrity, and ensure support reaches eligible Albertans faster and more efficiently.

Advancing AI Innovation Through Cross-Functional Collaboration (1)

Muhammad Soban Shoaib (Soban) will work alongside the Brilliant Harvest Team on the white label app shared component layer for web and mobile applications
Description: This project is to capitalize on the efficiencies of having our front end applications being in React and React Native. Due to the similarities of the two frameworks, it is possible to create components like dropdowns, buttons, pick lists and other function libraries that can be used by both the web and mobile apps, this reducing development and maintenance effort. Intern Soban will work under the tutelage of our senior devs to perform this work.
Nathaniel Dean will work alongside the Brilliant Harvest Team on the data ingestion pipeline output validation test automation project
Description: Our knowledge base of documents is the foundation of our assistant. The process of ingestion is performed by a number of processes, all of which can have failure points. This project will enable us more easily and accurately validate the output of our data ingestion process overall enabling us to scale more economically.

Snowb^rd: A Programming Language for Teaching

In 1982, Holt and Cordy created Turing, a programming language for teaching at the University of Toronto. It followed best software design practices and had a huge impact on the quality of learning.

At STaBL Foundation, we believe it is time to design a new programming language for teaching—Snowb^rd(TM)—to bring the leading edge of programming language and software design to children in primary school who know Scratch and are ready to move on to a text-based language—and support primary teachers by eliminating the dreaded “syntax error.” Snowb^rd will leverage the math children already know or can easily learn to understand the structure of programs. Every child learns set theory, and Snowb^rd will be the first language designed to leverage this knowledge by using a categorization of data called subtyping. Every child recognizes the idea of a directed graph (also called a network) as embodied in the “hidden map of an adventure game.” Snowb^rd will be the first language to use a type of directed graph to specify interactive behaviour—not as a form of documentation—but as an alternative, editable, and automatically synchronized view of (part of) the text program. And most importantly, every child needs to learn variables and functions to succeed in high school algebra, which is the bottleneck to all STEM careers and education pathways. Snowb^rd will be a functional language, which means that variables and functions behave the same way as they do in algebra, continuing the approach used to build up our Algebraic Thinking curriculum.

This Mitacs project will support prototypes for key features of Snowb^rd. Professors at McMaster University (Wolfram Kahl) and the University of Toronto (Anya Tafliovich and Edward Lee) will bring their teaching and programming-language theory knowledge, such as type systems, bidirectional type inference, and the Zipper data structure.

Stage en évaluation du potentiel minier 2026

Ce projet vise à donner des expériences de stage appliqué de 4 mois dans le domaine de l’exploration à des étudiants/étudiantes en géologie au niveau maîtrise. Ces stages seront accueillis par des compagnies d’exploration, d’exploitation ou de service basées au Canada à la recherche de différents types de minéralisation sur des propriétés minières dont le niveau de connaissance est variable. Le début du stage est marqué par une formation pratique sur des concepts théoriques et techniques de la géologie d’exploration au Canada et donnée à l’Université du Québec en Abitibi-Témiscamingue. Par la suite, les stagiaires seront déployés vers leur compagnie d’accueil respective. Faisant partie d’une équipe interdisciplinaire et supervisé par un géologue, les stagiaires participeront à des travaux de cartographie géologique, d’échantillonnage, de mesures de propriétés physiques, de caractérisation chimiques et minéralogiques et/ou de descriptions de forage dans le but de découvrir de nouvelles minéralisations, de définir les extensions de zones déjà connues ou de développer des méthodes d’analyses sur multiples support de matériaux. Ces stagiaires permettront aux organismes partenaires d’avoir accès à des étudiants/étudiantes en géologie dont le corps d’emploi est présentement en grande demande sur le marché du travail canadien.

Effects of Overspeed Sprinting in International Class Track and Field Athletes

Running speed is one of the most sought after abilities in sport with many coaches and athletes looking to improve it. This project aims to determine the effectiveness of overspeed training, a method used to make athletes run faster than they could on their own to improve speed. Little is known about how well this training works. This is because in the past the equipment needed to do this training was difficult to obtain and expensive. Today, the equipment is more accessible. This presents an opportunity to explore if this training works to improve speed. Through research and training interventions, the projects aims to assist Royal City Athletics Club in determining the value of this training. RCAC is one of Canada’s leading track and field clubs with athletes competing at the youth, development and international level. This research will help RCAC coaches deliver improved programming to their athletes at all levels. Between RCAC as a leader in Canadian track and field and the University of Guelph’s recognized research ability, the knowledge from this project can benefit sport science research across Canada in both track and field and other sports.