The proposed research focuses on developing a welding system that can be used to create helmet pads and other protective gear, like knee and shin pads. This system will use ultrasonic welding or soldering techniques, making the process more efficient than current methods. The goal is to reduce the time and labour involved in manufacturing […]

The research focuses on development and implementation of advanced software algorithms designed for the automated analysis of skin lesion images. The algorithms will be designed to run on mobile computing devices such as smartphones and tablets, and could be used by the general users as well as doctors for computer-assisted screening and diagnosis of skin […]

We propose the development and commercialization of biodegradable wastepaper foam as a viable alternative to traditional synthetic materials. Our solution aims to address the environmental challenges posed by non-biodegradable packaging materials while providing effective cushioning protection for a wide range of products, spanning from lightweight to heavyweight products.

In the complex and ever-evolving realm of shipping investments and operations, informed decision-making stands as a cornerstone of success. Within Soshianest Inc., the primary focus lies in providing precise and reliable freight rate forecasts. Through the utilization of state-of-the-art AI models, the company aims to enhance shipping strategies, enable data-driven decision-making, and adeptly maneuver through […]

Innovation in domains such as organic electronic materials is driven by experimental methods that are generally limited by the speed of human intervention in all the steps of the iterative R&D cycle. The emergence of AI tools and automated systems can now help to disrupt this paradigm by empowering the researcher to efficiently leverage their […]

Medical imaging is a cornerstone of modern healthcare, but challenges like high costs and limited accessibility hinder its potential. This project investigates the use of diffusion models—a cutting-edge AI technique—to generate synthetic medical images for targeted healthcare applications. By focusing on a single imaging task, such as cross-modal imaging or sequence generation, the project will […]

This project focuses on developing a smart, wearable system powered by artificial intelligence (AI) and advanced brain signal analysis to help monitor worker fatigue and stress in the mining industry. Mining is a demanding job, and workers often face long hours and stressful conditions, increasing the risk of accidents. The system uses a small, non-invasive […]

This project addresses the biotechnology and pharmaceutical industries’ need for mature, physiologically relevant cardiac models for drug discovery, cardiotoxicity testing, and personalized medicine. Existing models, such as human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), lack the structural and functional maturity needed for reliable applications. The UBC MEMS Lab has developed a soft, micropatterned substrate and a […]

In the field of speech-language pathology, the tongue’s role cannot be overstated. It is crucial for articulating speech sounds and ensuring the safe passage of food and liquids from the mouth to the esophagus. Yet, despite its importance, speech-language pathologists face significant challenges in evaluating tongue performance due to the lack of effective tools. This […]

This project aims to create engaging learning activities and a digital interface to help different groups of people understand and talk about important social issues like racism, ageism, cultural differences, and generational divides. The project will focus on four main groups: young children, high school or university students, community members, and workplace teams. By developing […]

Skin cancer, especially melanoma, is one of the most prevalent cancers worldwide, with North America experiencing particularly high rates. Despite the importance of daily sunscreen use, concerns about the safety of traditional UV filters—such as skin penetration and potential hormonal disruption—continue to grow. Additionally, these filters degrade when exposed to sunlight, reducing their effectiveness over […]

This project introduces a novel, fast, and selective method for detecting microplastics (MPs) in water sources, alongside other contaminants such as heavy metals. Utilizing a cost-effective microfluidic chip, the solution aims to provide affordable water monitoring while promoting habit changes in plastic product usage to support environmental sustainability.