L2M – SmartSustain Invest Copilot

SmartSustain Invest Copilot provides sustainable investing by combining advanced AI technologies with comprehensive ESG analytics and delivering cutting-edge portfolio management to individual investors. The platform transforms complex ESG data into actionable investment strategies, offering a sophisticated yet accessible solution for those seeking both financial returns and positive impact.

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L2M-Advanced Cell Culture System for Personalized Medicine

This project aims to commercialize a novel cell culture substrate designed to enhance cell functionality, bridging the gap between research and application. By addressing key challenges in disease modeling and drug discovery, this innovation holds the potential to revolutionize the industry, benefiting both academia and industry through scalable, effective solutions.

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L2M-Market Evaluation and Commercialization Strategy for APOBEC3-Targeted Therapies in Oncology

This project aims to assist a partner organization in evaluating the market potential of a novel APOBEC3 inhibitor as a cancer treatment. The focus will be on conducting comprehensive market research to understand the demand for this innovative therapy, explore its commercial viability, and identify potential partners in the biopharmaceutical industry. The project will assess […]

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Quantitative Digital Pathology Algorithm for an Automated Cancer Slide Imaging System

Digital Pathology provides a great reliable source for cancer diagnosis; however, this relatively new technique lacks an appropriate method of regulation and standardization. As a result the information obtained from cancer imaging system might suffer from inconsistency of the results (repeatability and reproducibility issues). Working with the BC Cancer Research Center, Logipath Medical Inc. has […]

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Dermoscopy Imaging and automated analysis for skin cancer screening

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 […]

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L2M-Sustainable Wastepaper Cushioning Foam and its Commercialization

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.

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L2M-Shipping rate forecasting using deep learning solutions

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 […]

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L2M-Image_Synthesize

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 […]

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AI & Chaos Theory-Powered EEG-Based Systems Predicting and Managing Worker Fatigue and Stress in the Mining Industry

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 […]

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L2M- FlexMatrix: Advanced Cell Culture System with Micropatterned PDMS Substrate and Biaxial Stretching

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 […]

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