Innovative Projects Realized

L2M – Auto Byuing Companion

This project aims to develop AutoBuyingCompanion (ABC), a digital advisory tool that helps Canadians make informed car-buying decisions. By processing user requirements, car specifications, and cost of use, as well as environmentally responsible usage, this project will provide recommendations on the most suitable models. By incorporating data analytics with insights from artificial intelligence, this project will enhance car-buying transparency, as well as simplify the comparison process for users. Indeed, the benefiting partner will be able to enhance its position in the industry with the scalable, friendly, and helpful car-buying system.

L2M-Blue Beauty Innovation: Sustainable Seaweed Bioactives for Cosmetics and Skincare

Title “Blue Beauty Innovation: Sustainable Seaweed Bioactives for Cosmetics and Skincare”
This project explores the potential of using natural compounds extracted from sugar kelp (Saccharina latissima), a seaweed that grows abundantly in Atlantic Canada, as safe and effective ingredients for skincare and cosmetic products. Around the world, consumers and companies are looking for cleaner, more environmentally friendly alternatives to synthetic chemicals traditionally used in beauty formulations. Sugar kelp contains valuable bioactive compounds including proteins, lipids, polysaccharides, minerals, and powerful antioxidants such as polyphenols, phlorotannins, and fucoxanthin that may offer benefits including skin protection, hydration, and anti-aging effects. However, it is still unclear whether these seaweed-derived ingredients meet the actual needs of cosmetic formulators, and whether there is a strong market demand for them. To address this, the project focuses on gathering market insights. Through interviews with businesses, researchers, clean-beauty brands, ingredient suppliers, potential customers, and other industry professionals, the project will seek to understand what cosmetic companies require from new ingredients, what challenges they face with current synthetic options, and whether sustainably sourced kelp bioactives could serve as a suitable solution. This includes learning about performance expectations, regulatory needs, pricing considerations, and supply-chain concerns. The results of this work will guide future product development by identifying where sugar kelp ingredients could realistically fit into the beauty market and what evidence would be needed to move forward. For the partner organization, the project offers meaningful benefits: it provides a clearer picture of customer needs, commercial opportunities, and potential early adopters in the cosmetics sector. It also outlines the next strategic steps required to bring an ocean-friendly, Canadian-sourced cosmetic ingredient closer to market readiness. Ultimately, the project supports both sustainable innovation and economic growth within Canada’s emerging blue-beauty and marine biotechnology industries.

L2M-An AI-powered interactive educational robot that engages learners at the young age through natural conversation, personalized instruction, and hands-on activities, adapting its teaching style to each child’s needs.

This project focuses on developing an innovative, smart, interactive toy robot for children aged 3 to 8. The robot combines emotional intelligence, educational content, and safety monitoring to provide a healthier alternative to mobile device usage. It serves as a companion that can recognize a child’s mood, offer adaptive learning activities, and detect environmental hazards such as fire, smoke, or toxic gases.
By integrating AI-based emotion recognition, interactive games, and parent–child communication features, this project aims to address the lack of multifunctional, development-oriented smart toys in the market. The outcome will include a validated product concept, a market analysis, and a commercialization strategy tailored to the Canadian smart toy industry. This work will support child well-being, enhance family safety, and contribute to Canada’s growing innovation ecosystem.

L2M – CO2 Loading Automated Tester

This project will explore the market needs for a new automated CO2 loading tester, a device designed to make carbon capture systems easier, safer, and more cost-effective to operate. The intern will interview potential users (e.g., engineering firms, research labs, and early adopters) to understand the challenges they face and the features they need most. The project will also evaluate different business models and identify the customer group most likely to benefit from the technology first. The outcome will be a clear commercialization roadmap that reduces uncertainty, supports informed product development, and helps bring this innovation to market more effectively.

Synthesis and Isolation of terminal carboxyl and pyridyl metal-organic cages

The objective of this project is to synthesize and isolate new heteroleptic metal-organic cages (MOCs) to function as reaction vessels for a series of different applications. The MOCs will consist of two triarylborane ligands and two triarylamine ligands for a ligand ratio of 1:1. Two separate cages will be explored with one consisting of ligands with carboxyl terminals, and the other with pyridyl terminals. These cages will provide different sizes and geometries based on the ligand to metal ratios and functionality of the varying ligand terminal groups. The MOCs will be used to explore charge-transfer fluorescence with potential in chemical sensing as well as host-guest chemistry with potential for FLP activity. Many systems involving charge-transfer and FLPs have been explored, but none of which have been developed into cage-like structures.

L2M – UV-Laser Based High-Resolution Hybrid Additive Manufacturing by Precise Material Dispensing

Our project is about a novel hybrid 3D printing system that combines the best parts of two popular printing methods: Fused Deposition Modeling (FDM) and Stereolithography (SLA). FDM printers can make large parts but with low precision and limited surface quality, while SLA printers create very accurate parts but waste a lot of resin and can only print small objects. This gap shows a clear need for a method that can produce large, high-quality parts without high material costs. We have already built and tested a proof-of-concept system that addresses this problem. It uses a custom nozzle and syringe pump to deposit small amounts of resin, which is cured by a laser in real time, reducing waste and enabling large, high-resolution printing at lower cost. The proposed project will now focus on a market assessment to understand who would benefit most from this technology and where it can provide the greatest impact. The partner organization will gain early insight into a new Canadian innovation, its possible applications, and opportunities to support future commercialization.

Predictive Processing of Disfluent Speech in Bilinguals

Language is one of the most fundamental cognitive processes, yet we know relatively little about how bilinguals learn, understand, and use language. This is a critical knowledge gap, as around 20% of Canadians grow up in bilingual homes. Furthermore, what we do know about bilingual language acquisition has focused on fluent language. Speech disfluencies (e.g., uh and um) can aid language processing in adults, as experienced listeners harness an association between disfluency and hard-to-produce words to make predictions for what a speaker will say next. Here, we investigate how age and exposure to a second language impact disfluent language processing. We emphasize the role of prediction making, hypothesizing that older children with more exposure to a target language will use speech disfluencies to anticipate what a speaker will say next. We also make a methodological contribution by testing and refining methodological tools, focusing on how eye-tracking can be used to measure prediction making. This project unites two bilingual language acquisition labs at Concordia University and the University of Wisconsin. Through this project, the two labs will be able to investigate bilingualism across a diverse set of participants and develop analytical tools that will support the ongoing work of both labs.

Enhancing Health Practitioners’ Engagement in Digital Behaviour Change Programs: The EVO+ Colombia Case

The project aims to design and test a strategy that helps healthcare workers introduce and follow up on the use of the EVO+ Colombia app, a digital program that supports people in building healthier habits related to eating and physical activity. By understanding what makes it easier or harder for health workers to recommend and monitor the app, the team will create tools and approaches that fit their daily routines. Participating institutions—both in Canada and Colombia—will benefit from stronger collaboration, new knowledge about how to support behaviour change through digital tools, and practical interventions that can improve patient care and the successful adoption of health programs within their services.

L2M-Body-Safe Wearable Antenna Technology for Reliable Health Monitoring Devices

This project focuses on validating the real-world potential of a new wearable wireless sensing technology designed for safer and more reliable on-body communication. Many current wearable devices struggle with performance instability and safety issues due to strong interaction with the human body. This project explores an alternative design approach that minimizes unwanted radiation into the body while maintaining accurate sensing and communication capabilities.

Over a four-month period, the project will involve customer discovery, market research, and business model development to understand where this technology can create the most impact — particularly in healthcare monitoring, rehabilitation, and smart wearable applications. The goal is to bridge the gap between academic research and real-world application by assessing user needs, industry interest, and commercialization pathways.

This work supports the development of safer, more efficient wearable technologies and contributes to Canada’s innovation ecosystem by advancing research translation into practical solutions.

L2M – AI-powered Vision-based Robotic System for Autonomous Waste Sorting and Recycling

Waste sorting today is inefficient and relatively expensive since current systems can’t achieve full autonomy. Our project introduces a practical solution that combines AI-powered vision-based object detection with low-cost robotic manipulators to automatically detect and sort waste streams in real time. This innovation reduces hardware and maintenance costs, minimizes the labor reliance, and greatly enhances the overall efficiency. By embedding robotics and AI into waste processing, we deliver a reliable and economically accessible recycling approach that promotes the circular economy and reduce landfill dependency.

L2M – Molecularly imprinted polymers optimized by Hansen solubility parameters for the extraction of phenolic compounds from water samples and water safety monitoring by LC-MS

Monitoring water quality is essential for protecting public health and the environment, yet many harmful pollutants remain difficult and expensive to detect. Among them, phenolic compounds commonly released from industrial activities are persistent, toxic, and often found in Canadian water systems at levels that require advanced laboratory testing. Unfortunately, current sample-preparation methods used to extract these pollutants from water are slow, costly, and not selective enough to reliably detect them at trace levels. These limitations create challenges for environmental labs, municipalities, and industries that are responsible for water safety monitoring.

This project aims to address these challenges by developing a new, more efficient extraction technology using Molecularly Imprinted Polymers (MIPs). These are synthetic materials designed with highly specific “binding sites” that recognize and capture phenolic pollutants, functioning like a lock-and-key system. Unlike conventional approaches, MIPs can provide stronger selectivity, better sensitivity, and lower cost over time because they require less solvent and preparation.

A key innovation in this project is the use of Hansen Solubility Parameters (HSPs), a scientific framework that predicts how polymers and solvents interact. By applying HSPs, we can design MIPs in a more accurate and data-driven way that are better suited for real-world water testing.

L2M – GutSight

This project will help develop GutSight, a new test to monitor inflammation in people with inflammatory bowel disease (IBD) without relying only on colonoscopies. Over four months, I will improve the way we measure gut biomarkers, strengthen the computer model that predicts disease activity using data from 400 patients, and do basic research on how this test could fit into real hospital and lab routines. The partner organization will benefit by getting a clearer picture of whether this test is practical, useful for doctors and patients, and worth developing further as a future product.