Mechanistic characterization of mixture toxicity of different cannabinoids

This project will investigate how mixtures of select cannabinoids affect different types of human and animal cell lines. As the use of cannabinoid-based products continues to rise in both Canada and Germany, there is a growing need to understand potential health impacts, especially when multiple cannabinoids are present together. By studying mixture toxicity rather than […]

Read More
An ensemble machine learning framework for streamflow data reconstruction

This project will develop a new framework to reconstruct missing streamflow data using advanced machine learning techniques. Reliable streamflow records are essential for flood forecasting, drought monitoring, and water resource planning, but many stations have missing or incomplete data. The proposed approach will combine traditional statistical methods with modern single-learner and ensemble machine learning models […]

Read More
Phylogenetic homogenization or differentiation in global urban non-native floras: decoupling environmental, spatial, and connectivity drivers

This project will investigate whether urban plant communities composed of non-native species around the world are becoming more similar to each other or remaining distinct due to environmental, spatial, and connectivity constraints. Using the Global Urban Biological Invasions Compendium (GUBIC), the study will compare plant assemblages across cities to understand how climate, urban characteristics, and […]

Read More
L2M – Construction Equipment Tracking Market Research

TAUlab is building a fleet and equipment-tracking platform for small and mid-sized construction contractors. These companies often struggle with lost equipment, incomplete job-site reporting, and administrative overload. Although many large enterprise tools exist, they are bloated with features and rarely match how smaller subcontractors actually work day-to-day. Most companies in this segment still rely on […]

Read More
L2M – Expert Validation of IPPM Now and Assembly of a Smart Trap Prototype

This project will help Insect Track Solutions improve and validate IPPM Now, a digital tool designed to make insect monitoring easier and more accurate for farmers, agronomists, and researchers. Today, insect data is collected in many different ways, making it hard to compare results or make fast decisions. The project will work with expert users […]

Read More
Enhancing Sawmill Residue Utilization Through Mobile Biochar Production

This project will demonstrate on-site biochar production from sawmill residues at Patterson Sawmill (Hay River, NWT) using Saskatchewan Polytechnic’s mobile kiln. The mobile system avoids high transport and capital costs associated with stationary facilities and can process diverse residue types directly on-site, offering a practical solution for sustainable management of waste biomass at northern sawmills. […]

Read More
L2M – Commercialization of Cold Plasma Technology for Sustainable Disinfection in Agri-Food Applications

Disinfection is essential across households, industries, agriculture, and healthcare. But, choosing the right chemical disinfectant raises concerns, as residues, volatile compounds, and microbial resistance often force us to switch chemicals or increase dosages. What if we could disinfect without adding chemicals? Our project explores this possibility by altering the chemistry of air and water using […]

Read More
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. […]

Read More
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 […]

Read More
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 […]

Read More
L2M- Potatoleaf Doctor( AI model for potato leaf detection)

Agriculture supports food security for 60% of the global population, with potatoes, the 4th most consumed crop, feeding around 1.5 billion people daily (Afakh et al. and LeCun et al.). Canada produces about 5.7 million tonnes of potatoes each year, making it the 12th-largest producer in the world. The country’s potato exports generate around $1.6 […]

Read More
Grid integration, analytical assessment, and optimization of the KETTI-developed wind turbine.

The proposed project aims to establish a technical and scientific foundation for integrating KETTI’s innovative wind turbines into the Microgrid Research and Testing Facility at the University of Regina (UofR). The research involves three complementary subprojects: 1. Feasibility and Engineering Requirements Study — defining the integration framework, electrical and mechanical interfacing, and environmental conditions necessary […]

Read More