Grants and Contributions

The CRCLR Resource Use Efficiency & Hardware Optimization Project aims to transform the growth performance of leafy greens and strawberries, amongst other crops, by addressing hardware deficiencies and optimizing resource use.

An AI based software development project to enable coaches to deliver assessments that elevate athlete progression and save coaches time.

SyncMed Technologies Inc., a medical emergency s/w company, will develop a functional AI prototype that passively captures ambient speech during EMS calls and generates structured Trauma Report content. This project will test the feasibility of integrating speech-to-text and natural language processing (NLP) pipelines into EMS workflows, laying the foundation for scalable AI modules within the EMS2ED platform. The outcome will validate SyncMed’s capacity to support real-time clinical handovers with AI-driven documentation tools.

Design, build and test a system for inspection of one-sided welds.

This Canada–Germany collaboration aims to accelerate the discovery of next-generation lithium-ion battery materials by integrating self-driving laboratories (SDLs), advanced diagnostics, and AI. The project focuses on optimizing cathode–electrolyte combinations to improve battery performance, safety, and longevity. Using rapid electrochemical impedance spectroscopy (EIS), high-throughput characterization, and AI-guided optimization, the team will develop and validate materials and methods for scalable production. Partners include Pulsenics, NRC, McMaster University, Preli GmbH, and Helmholtz-Institute Münster/FZJ.

Antimicrobial resistance is a top 10 global health threat and innovations are required to combat a silent pandemic expected to cause more deaths than cancer by 2050. A leading candidate is the use of the oldest natural enemy of bacteria—their own viruses called bacteriophages or phages. There are no specific clinical criteria for bacteriophage susceptibility and testing with routine methods is cumbersome and manual. This Project proposes the use of a microfluidic device to screen bacteriophages for E. coli, Staphylococcus (including methicillin-resistant S. aureus), and Pseudomonas (including P. aeruginosa). This device expands on Sci-Bot technology using two fluorescent detectors for a screen of up to 30 phages in as little as 3 hours, to a tailored digital microfluidic chamber allowing for single droplet analysis, titration, and synergy. This builds on work with HHT and CRAFT colleagues and will be expanded to an NRC and Innovate UK collaboration on phage production.

The Project will support pilot testing of AI strategies, determine target architecture and quantitative technical objectives for implementation of an AI solution.

Project to push Gambit from purely AI based conversations to integrated context specific workflows.

The project aims to enhance and adapt the current version of the firm's app to fit the clinical needs of adult spine deformities, resulting in a significant expansion of addressable market and revenue potential.

The project aims to enhance machine perception so it can reliably distinguish between an actual wildfire and harmless heat sources such as hot rocks, barbecues, hot tubs, or vehicles. Making this distinction is critical to ensure water or fire suppressant is applied only where needed, minimizing waste and preventing unnecessary damage.