L2M – Smart Textiles And Autism Spectrum Disorder

This project will validate an inclusive, wearable feedback system designed to support emotional regulation by detecting stress, mapping emotions, improving emotional communication, and preventing burnout and meltdowns. It is especially relevant for individuals with autism, ADHD, and sensory sensitivities, offering discreet, real-time feedback that enhances emotional awareness and expression. Grounded in ethical and inclusive design, […]

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L2M – NeurolAssist

We are developing a specialized AI-driven Clinical Decision Support System (CDSS) for neurology that integrates a large language model with domain-specific tools (such as neuroimaging analysis, EEG interpretation, and up-to-date medical knowledge retrieval). The system serves as an intelligent assistant for neurologists, helping analyze patient data (e.g. MRI scans, EEGs, clinical notes, etc.) and providing […]

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L2M – LeanPrompt: Accelerating Generative AI with Smarter Resource Utilization

We aim to develop and implement a cost-efficient framework for communicating with proprietary generative AI platforms such as ChatGPT. In fact, these provider companies expose their models through an interface that can be accessed via API. However, calling their API will incur a cost considerably based on our request. Basically, smaller models are cheaper than […]

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L2M – AllerEase: Personalized Allergy-Safe Grocery Tool

AllerEase is a personalized grocery recommendation tool that helps allergy-sensitive users shop safer and easier. It generates user-specific shopping lists based on allergy profiles and live product data. This project aims to refine matching logic and validate usability through real-world testing.

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L2M – Enhancing 3D Bioprinting with Advanced Nanofillers for Regenerative Medicine

This project focuses on developing advanced bioinks enhanced with tiny filler materials to improve 3D bioprinting for tissue engineering. By creating stronger, more printable, and biologically compatible materials, the project aims to help the partner organization advance regenerative medicine technologies. This will support the development of new personalized medical treatments and open up commercial opportunities […]

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Biomass-waste derived Quantum Dots nanocomposite-based electrochemical sensor for detecting emerging pollutants

Emerging contaminants (ECs) have become a significant environmental concern due to their widespread presence and risks to health and ecosystems. Meanwhile, agricultural waste is also increasing, providing a valuable source for high-value materials. Traditional detection methods are costly, slow, and require specialized equipment and time-consuming laboratory analyses. Electrochemical sensors offer a low-cost, rapid, and sensitive […]

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TRLUP – Head First Care

This project will support the development of an accessible, digital tool designed to help people recovering from concussions, especially students and older adults by offering step-by-step guidance and resources. Through this internship, we aim to finalize our MVP (minimum viable product) and research the best rehabilitation technologies to include on the platform. By helping advance […]

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TRLUP – Apex Health Digital Health Platform enabling global health record accessibility

Apex Health is an emerging Canadian digital health company dedicated to advancing equity, security, and innovation in health information management and informatics. Its operations are focused on delivering privacy-first digital health solutions, including health data analysis using machine learning and predictive analytics. Apex Health is committed to helping Canadian healthcare organizations optimize clinical outcomes, enhance […]

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TRLUP – Quinan Labs, Agentic AI Technology

This project is focused to democratize enterprise-level information technology solutions for Atlantic Canadian small and medium sized businesses (SMBs) through a revolutionary one-person or small team, agile, artificial intelligence (AI)-powered consultancy model. This project will provide key innovation using cutting-edge AI tools (Claude, agentic AI), which can deliver digital transformations at 1/10th the traditional cost […]

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Towards Sustainable Nowcasting: Exploring Lightweight Models for Local Precipitation Forecasting

This project focuses on investigating more efficient and simplified approaches for very short-term precipitation forecasting, known as nowcasting. The goal is to evaluate and adapt lightweight machine learning models that can deliver accurate predictions using fewer computational resources. By reviewing existing models, testing their performance, and exploring ways to simplify their architecture without losing accuracy, […]

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