Enhancing Privacy Against Surveillance and Censorship in Future Internet Architectures

The dramatic growth of the Internet has enhanced access to information, fostering seamless communication and promoting effective collaboration. Unfortunately, advanced network traffic control and monitoring systems have empowered state-level actors to deploy large-scale surveillance and censorship mechanisms that track people’s Internet activities or limit their ability to freely access and publish information. Recently, multiple initiatives […]

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Cultivating Financial Literacy & Mentorship for Indigenous Communities – IndigenousTech.ai – May 5-Aug 29

Since our company was founded, IndigenousTech.ai Corporation (IndigenousTech.ai) has focused on improving the quality of life for Indigenous peoples living on reserve. To advance economic development, self-determination, and reconciliation of Indigenous communities in Canada, our company offers financial literacy training, housing reviews, credit projects, implementations of new technologies for remote communities, professional skills, and mentorship […]

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Enhancing QML trainability in noisy quantum systems

This project will develop novel circuit metrics to predict model performance under realistic noise conditions, offering a practical approach to enhancing QML trainability. The research will investigate optimal parameter resilience across different circuit depths, qubit counts, and problem types, while comparing overparameterized and underparameterized regimes. Additionally, circuit metrics will be developed to predict model performance […]

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Automatically Evolving Machine Learning Codebases with Large Language Models

Machine learning (ML) is transforming industries like IT, finance, and healthcare, but the code that powers these systems is still mostly written and updated by hand. This project explores how Large Language Models (LLMs) can assist developers by predicting and suggesting code edits for ML projects. By analyzing real-world code from public repositories, the research […]

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A Patient-Centered and Visually Attractive Toolkit Adapted to Children and Youth to Reduce Inhaler Impact on Carbon Footprint in Ambulatory and Outpatient Settings

A Patient-Centered and Visually Attractive Toolkit Adapted to Children and Youth to Reduce Inhaler Impact on Carbon Footprint in Ambulatory and Outpatient Settings 1) Introduction/Background: Carbon footprint (expressed in carbon dioxide equivalent, CO2e) is the preferred method to measure our impact on climate change. Healthcare represents 4.6% of total Canadian greenhouse gases emissions, and in […]

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Leveraging AI and IoT to predict heatwaves in Canada: A climate health initiative

This project uses AI and smart thermostats to predict heatwaves in Canada, helping protect public health. By analyzing indoor and outdoor temperature data, we aim to improve heatwave forecasting and understand how extreme heat affects indoor spaces. Using machine learning, we develop models to predict future indoor temperatures, supporting better planning and response strategies. The […]

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L2M_Business Strategy for CELLECT’s Research and Commercialization

Despite advancements in women’s health diagnostics, cervical cancer screening rates remain critically low due to the invasive nature of traditional collection methods like Pap smears and self-swabs. CELLECT is pioneering a non-invasive, nanotechnology-enabled collection device—the CELLECTPad—that passively captures high-quality cervical and epithelial cells during menstruation. By removing the discomfort and accessibility barriers of existing methods, […]

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Cross-Cultural wisdom: Mapping wise strategies for life’s major decisions

This project explores how people from different cultures make important life decisions, such as career choices or relationships. It focuses on understanding how cultural norms, social values, and religious beliefs influence decision-making. The research will use advanced text analysis (Natural Language Processing) and surveys to identify patterns in how people from different backgrounds approach decisions. […]

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Biosignal Transformers for Advanced Blood Pressure Waveform Analysis

This project aims to develop advanced machine learning models to analyze arterial blood pressure (ABP) waveforms from patients in intensive care units (ICUs). By using a large dataset and cutting-edge techniques like transformer architectures and contrastive learning, the goal is to create models that can accurately predict patient outcomes, such as ICU mortality and hospital […]

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Algorithms and Software System for Analysis of Twitter Data using Apache Spark

The goal of this project is to develop a software system to collect, store, organize and query Twitter messages, and to develop algorithms that can process the Twitter data to extract value-added information, in particular, the geolocation of Tweets. First, we will design and implement a processing and analytics system for Twitter data using the […]

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Enhancing light-matter interactions with intercalated transition metal dichalcogenides

This research project pioneers the development of novel molybdenum disulfide (MoS2)/copper hybrid materials through electrochemical intercalation and exfoliation techniques. By transforming readily available powdered molybdenite—a byproduct of Canadian mining operations—into atomically thin layers with enhanced properties, the work creates a sustainable pathway for producing high-performance two-dimensional materials without organic additives that typically compromise conductivity. The […]

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Implementing a Computer Vision-based Collision Avoidance System for a Collaborative Surgical Assistant Robot

This project aims to enhance the safety, precision, and efficiency of robotic surgical assistants — collaborative robots designed to work alongside surgeons — by developing a computer vision-based system that prevents collisions in real time. Using cameras and advanced image processing techniques, the system will monitor the operating room, detecting people and other obstacles. It […]

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