Projets novateurs réalisés

L2M – Clarify Student Resources

Canada’s education system is facing mounting challenges. Educators are reporting high levels of stress and burnout, largely due to administrative burdens that take time away from teaching. Simultaneously, students—particularly in STEM subjects—are struggling to keep pace in a system that often lacks the capacity to provide individualized support. These issues are especially pronounced in under-resourced and rural communities.

To address these challenges, this project will develop Clarify, an AI-powered education platform designed to streamline teacher workflows and enhance personalized learning for students. Clarify automates time-consuming tasks such as grading and lesson planning while generating data-driven insights into student performance. At the same time, it provides students with adaptive study plans tailored to their unique learning styles, strengths, and needs.

The project will focus on designing, building, and piloting a Minimum Viable Product with key features including AI-assisted auto-marking, personalized study tools, and performance analytics. Through pilot programs in schools across Nova Scotia, Ontario, and British Columbia, the platform will be refined using feedback from educators, students, and administrators. Data privacy and alignment with provincial education standards will be central to the platform’s design.

This initiative goes beyond typical educational software development by integrating expertise in artificial intelligence, user-centered design, and educational psychology. It aims not only to reduce administrative burden, but to support more meaningful teacher-student interaction and improve student outcomes—particularly in areas where traditional supports are limited.

With iterative improvements, the project will be positioned to transition from development to real-world implementation. In doing so, it contributes to a more equitable and effective education system, improves workforce readiness, and strengthens Canada’s position as a leader in education innovation.

L2M – BioThera Solutions

Our project aims to revolutionize the anti-aging skincare market by developing a breakthrough delivery system that enhances the absorption of active ingredients at the cellular level. Traditional skincare products often fail to penetrate deep enough to provide lasting results, leaving consumers with temporary fixes. By leveraging innovative biotechnology, our solution ensures more profound skin rejuvenation, reducing the need for costly or invasive procedures. This project will provide a cutting-edge product that meets the growing demand for effective, science-backed anti-aging solutions, positioning us, BioThera Solutions, as an innovative leader in the $44 billion anti-aging skincare market.

Signal/Noise analyzer for EM Telemetry tool

The ultimate objective of this project is to design and develop a signal/noise analyzer to improve the reliability and efficiency of EM-based measurement-while-drilling (MWD) tool within various strata formation under high temperature, deep drilling environment. In order to analyze the received signal contaminated by surface and underground noise, it is essential to understand the electrical and magnetic field behavior with respect to rock formation and the transmitted signal properties including frequency, amplitude, and phase. In this regard, the main focus of this research project is dedicated to study, analysis and simulation of electrical properties of the underground strata formation in drilling environment such as conductivity, dielectric constant, permeability, permittivity, and resistivity. This four-month project includes research and study on previous works and literatures; papers, patents and textbooks and modeling, and computer simulation of induced current penetration under different drilling environments.

Biomolecular characterization of micro-organisms associated with the rhizosphere of five economically important Andean crops as an assessment of soil health and productivity

The project has five steps: 1. Identification of the microbiota associated with the rhizosphere of five economically important crops in the province of Chimborazo, Ecuador; 2. Isolate and select micro-organism strains that are likely to contribute efficiently to the development of the crops; 3. Using field trials, determine the efficiency of the selected micro-orgranisms; 4. Knowledge transfer and report writing. The intern will arrive to undertake steps 3 and 4. The lead investigator is part of a research team in adaptation to climate change based at ESPOCH in Chimborazo. I have worked with the team for over five years and it emphasizes international collaborations. The intern will be part of a team of undergraduate students and will build research skills that can be applied to soil research in the Thunder Bay area.

L2M – Scaling Sustainable Waste-to-Energy Solutions: Poultry Manure to Biofuels and Carbon Capture

The project “Scaling Sustainable Waste-to-Energy Solutions: Poultry Manure to Biofuels and Carbon Capture” focuses on commercializing an innovative pyrolysis-based technology that transforms poultry manure into bio-oil, biochar, and pyro-gas. This solution addresses both environmental and economic challenges in Canada’s poultry and renewable energy sectors by providing a sustainable alternative to traditional manure disposal methods, which contribute to high greenhouse gas (GHG) emissions and nutrient runoff pollution. Through controlled thermochemical conversion, this technology reduces waste disposal costs for farmers, mitigates up to 25,000 metric tons of CO2-equivalent emissions annually, and creates new revenue streams. The resulting bio-oil serves as a renewable industrial fuel, while biochar enhances soil quality and enables long-term carbon sequestration. Pyro-gas, a valuable byproduct, can also be reused within the system, improving energy efficiency. The project aligns with Canada’s 2050 net-zero targets and advances circular economy principles by converting agricultural waste into valuable resources. Over the four-month Lab2Market program, the focus will be on market validation, regulatory compliance, intellectual property protection, and financial feasibility analysis, ensuring that the technology is commercially viable and ready for industry adoption. By collaborating with key industry partners such as Net Zero Atlantic, this project will help position Nova Scotia and Canada as leaders in sustainable agri-tech and clean energy innovation.

L2M – Craft Brewery Innovation Project

Craft breweries depend heavily on their brewmasters to forecast demand and plan production, which distracts them from their core focus: brewing good quality beer. It also puts significant pressure on breweries because if the brewmaster suddenly becomes unavailable, they would be incapable of effectively completing these tasks. Forecasting and production planning become increasingly difficult as breweries grow operations, necessitating a better, tailored solution for craft brewery production planning automation and standardization.

We provide a platform that helps breweries become self-sufficient and facilitate their production and operational growth. In a user-friendly web application, brewers can generate seasonal, monthly and weekly demand and sales forecasts to better prepare their production, ensuring sufficient inventory levels and appropriate scheduling to meet demand. The application also automatically generates production schedules, ensuring demand is met efficiently. This enhances the brewery’s forecasting and scheduling process by providing greater confidence in accuracy, removing much of the reliance on a single individual to complete the process, and gives brewers more time to do what they do best – making great quality and delicious beer. The tools on the application are facilitated by a combination of machine learning, analytic and optimization-based algorithms to perform forecasting and scheduling. This project enables resource-scarce breweries to adopt advanced forecasting and scheduling technology without requiring deep technical expertise, reducing reliance on manual planning.

We are performing a case study with a craft brewery in Nova Scotia for testing and refining our prototype, and we aim to develop at least two more industry partnerships through this program. We are nearing completion of a prototype and will soon begin testing, using real brewery data to validate our approach and refine key performance criteria. Through this program, we seek guidance in positioning and selling our platform to breweries, strengthening industry relationships, and gathering feedback to further enhance our product.

L2M – Shelltech_Business_Strategy_Internship_Proposal

This project will create an AI-powered device that helps shellfish hatcheries keep their larvae healthy by constantly monitoring them. The system uses smart image analysis to catch early signs of disease or stress, sends real-time alerts to staff, and reduces the need for manual checks. This makes hatcheries more efficient, helping them produce more healthy shellfish while saving time and money. By improving shellfish farming, this innovation supports Springboard Atlantic’s mission to connect research with industry and strengthens Canada’s aquaculture sector, boosting the economy.

L2M – Chase Biotherapeutics: Breaking barriers towards clinical translation of ChASE37-AR for stroke recovery

Stroke is a leading cause of disability, affecting 880,000 Canadians, with 109,000 new cases annually and no approved therapies for neuroregeneration. Current standard of care for ischemic stroke includes acute thrombolysis and/or thrombectomy to restore blood flow to the injured tissue, yet these treatments are time sensitive and only apply to specific stroke etiology, leaving over 85% of stroke survivors solely with rehabilitation, which is time and labour consuming and often plateaus within the first year. This leaves many individuals with lifelong disabilities and a reduced quality of life. Beyond the financial costs, stroke imposes devastating emotional, physical, and social burdens on both patients and caregivers. Despite decades of research, no approved therapies exist to regenerate lost brain tissue or restore lost function. The economic burden of stroke is $3.6 billion CAD annually in Canada alone, and is rising due to the aging population. The global stroke treatment market, valued at $36.1 billion CAD in 2022, is projected to double by 2032, reflecting a growing demand for innovative recovery therapies.
Chase Biotherapeutics is developing ChASE37-AR, a unique and disruptive regenerative therapy that combines a re-engineered enzyme (ChASE37) with a biodegradable hydrogel for sustained, localized delivery, comprised of 3 patents. Unlike existing treatments that focus solely on symptom management or rehabilitation, our approach is disease-modifying — actively promoting tissue regeneration and functional recovery by breaking down inhibitory barriers in and around the injured site. Our preclinical studies demonstrate that ChASE37-AR effectively enhances brain plasticity and improves functional outcomes in stroke-injured rats.
In this project, we aim to move closer to clinical translation, by initiating regulatory frameworks, developing a business plan, and further validating our technology in animal models. By achieving our goals, we will be well-positioned to advance ChASE37-AR into clinical trials and towards commercialization, ultimately transforming the treatment landscape for stroke.

L2M-Free Flow Counterflow Gradient Focusing

Our project focuses on improving protein purification using a novel continuous separation method; Free-Flow Counterflow Gradient Focusing (FF-CGF). Traditional purification methods are slow, inefficient, and result in high sample loss, making it difficult for industries like pharmaceuticals and biotech to recover valuable proteins. Our technology offers a faster, more efficient alternative without the need for costly additives. The project focuses on validating market demand, refining our business model, and developing a strategy to overcome commercialization barriers by seeking industry insights from stakeholders in the protein purification sector

L2M – High reliability free-space quantum communication in turbulent environments.

The objective of the proposal is to enable high-reliability free-space quantum communication in turbulence environments. Free-space optical and quantum communications face a critical hurdle of atmospheric turbulence induced distortions in propagating optical beams. This degrades signal purity in quantum key distribution (QKD) and long-distance optical transmission. Our vision for this project is to establish a fast physics-based turbulence prediction system for a secure free-space optical communication. This will extend the range and reliability of existing optical and future quantum communication networks. The turbulence prediction system can be an essential element of the design cycle and additionally be used in the signal deconvolution during operation of the receiving systems. For commercializing the idea, we require access to potential users of the proposed technology, so as to fine tune the system to the present needs of the industry, while working towards the future advancements in terms of key-exchange rate and transmission distances.

Magnetic Compression and Stability of Spheromaks

The objective of a fusion device is to confine a plasma and heat it to a temperative high enough for its ions to gain sufficient energy to overcome their mutually repulsive force and fuse. Fusion neutrons will provide a heat souce that’s used to generate electricity in a steam cycle. Fusion power is environmentally friendly and the fuel source is abundant. A spheromak is a toroidal plasma configuration that has internal currents to maintain the magnetic field that keeps it together. Several methods are used to compress spheromaks at General Fusion. Sufficient compression can cause the conditions to vary, instabilities that cause the spheromak to lose confimenent may develop. The magnetic compression experiment at General Fusion had the aim of producing spheromaks and then compressing them with an external pulsed magnetic field. During compression, the properties of plasma must be monitored to gain insights to mechanisms that can be implemented to optimize the compression process while maintaining the stability of the spheromak. The project will contribute to and advance existing spheromak technology at General Fusion.

Canada Trade Promo Optimization (TPO) Transformation: Modernizing the End-to-End Pipeline

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The main activities of the partner
Unilever Canada is a global leader in the consumer packaged goods (CPG) industry, focusing on innovation and sustainability across its five business groups: Beauty & Wellbeing, Personal Care, Home Care, Nutrition, and Ice Cream. The company integrates AI and data-driven approaches to optimize supply chain processes, improve consumer insights, and enhance business operations. A key focus is Trade Promotion Optimization (TPO), where Unilever applies machine learning techniques to enhance promotional efficiency. In this project, Unilever will provide industry expertise, access to proprietary datasets, and business insights to ensure the research aligns with real-world applications.
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The challenges the partner aims to solve through this project
Unilever faces challenges in scaling AI-driven trade promotion strategies across its diverse portfolio of 400+ products. Traditional trade promotion planning is inefficient, requiring extensive manual effort and struggling to balance multiple business goals, such as maximizing ROI, increasing market share, and reducing trade spend. Existing machine learning models also suffer from computational inefficiencies, limiting scalability. Additionally, integrating multi-objective optimization algorithms with real-time data analytics remains a complex challenge. This project aims to refine Unilever’s predictive models and streamline the end-to-end ML pipeline to enhance decision-making efficiency.
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The anticipated social or economic benefits of the project for the partner organization(s)
For Unilever, this research will lead to the development of an AI-powered TPO system, enhancing decision-making, reducing operational inefficiencies, and improving promotional effectiveness. Automating trade promotion planning will result in cost savings, higher profitability, and better allocation of marketing budgets. More broadly, society benefits from optimized trade promotions that improve product availability, create cost savings for consumers, and contribute to a more sustainable and efficient retail supply chain. Furthermore, advancements in AI-driven decision-making from this project could set a benchmark for other industries seeking to improve operational efficiency through machine learning.