L2M- AI Lab Assistant

This project initially targets drug discovery labs, with long-term plans to expand into broader biomedical research. As AI becomes integral to scientific work, we aim to build a custom AI assistant that goes beyond basic chat support, capable of running code, executing ML/DL pipelines, and assisting with lab-specific tasks.

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L2M – U-Pro Soccer

U-Pro Soccer is a Canadian sportstech company developing a mobile-first training platform that uses AI and computer vision to help youth athletes practice soccer drills at home using only a smartphone and a training mat. Many young players lack access to structured training, especially outside of team environments, and U-Pro aims to fill this gap […]

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L2M – Validating Nanobubble Technology for Sustainable Water Use in the Canadian Ecosystem

This project focuses on exploring how a new water based technology—called a nanobubble generator—can help solve common challenges in agriculture, aquaculture, and water treatment across Canada. Nanobubbles are minuscule gas bubbles that improve water quality by increasing oxygen levels, cleaning surfaces, and reducing the need for harmful chemicals. While this technology has seen success in […]

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L2M –Sustainable alternative supplementary cementitious materials using oat husk

This project explores innovative ways to convert agricultural residues (i.e., oat husks) into sustainable construction materials. Specifically, the research focuses on developing and validating cement replacement products derived from agro-waste, which can help reduce the carbon footprint of concrete, a major contributor to global greenhouse gas emissions. The intern will work closely with both academic […]

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Early Detection of Grain Spoilage and Contamination Using Hybrid NIR-E-Nose Systems with Machine Learning

This project explores the feasibility of using a hybrid sensing system that combines Near-Infrared Spectroscopy (NIR) and Electronic Nose (E-Nose) technologies, enhanced by machine learning, to detect early signs of spoilage and contamination in stored grains. By analyzing changes in grain structure and gas emissions, the study contributes to ongoing research on reliable, non-destructive, and […]

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Forecasting Levodopa-Induced Dyskinesia in Human Subjects with Parkinson’s Disease

We have developed a novel data augmentation procedure that significantly enhances machine learning-based classification of different brain imaging scans. Having successfully demonstrated proof-of-concept in a rodent model, we are now expanding this approach to clinical applications in humans. Specifically, we aim to utilize this technology to identify early biomarkers of neurodegenerative diseases, enabling personalized treatment […]

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L2M – GradFinder

We are building GradFinder, an online platform that connects students with professors who are actively recruiting for thesis-based graduate programs. Many students struggle to find available positions, and professors are overwhelmed by unqualified inquiries. Our platform streamlines this process, improving access and efficiency on both sides. Through this project, we aim to refine our business […]

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L2M – Creditcliq

Creditcliq is a fintech solution designed to help newcomers to the U.S. and Canada access financial products like credit cards, loans, and rentals by sharing their home country credit history with local banks and credit unions.

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Addressing Basis Risk in Agricultural Index-Based Insurance

The objective of the proposed research is to design and implement an innovative IBI scheme capable of minimizing basis risk. Forage insurance will be used as an example to empirically examine the effective implementation of the IBI, through establishing an adequate relationship between the weather index and forage yield. Therefore, a second objective of the […]

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3D printed concrete construction

This project will contribute to developing design guidelines for steel-reinforced 3D printed concrete structural members. 3D printing is a novel construction method that is being developed around the world. It has the potential to revolutionize construction practices, because it is an automated process that requires less heavy labor compared to regular construction practices. The material […]

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L2M – Intelligent Bearing Prognostics and Health Monitoring System

Bearings play a critical role as fundamental mechanical components in rotating systems. Any imperfections, such as inadequate lubrication, can gradually result in failure. Industry reports indicate that 40-70% of failures in rotary systems are attributed to bearing failure. The sudden occurrence of such failures poses significant challenges for industries, resulting in decreased profitability, and various […]

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