Improving technology for identifying environmental microplastics with machine learning

The average human consumes a credit card worth of plastic every week as a result of environmental microplastics. The tools and technology that are currently used to analyze chemical compound structures to identify polymer types in microplastics research are not well-calibrated for field-specific use. Raman spectroscopy data from microplastics samples is imperfect. Furthermore, plastics that […]

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AI-driven evaluation of clinical electroencephalographic (EEG) recordings

The proposed project is part of a large-scale collaboration between SFU’s Behavioral and Cognitive Neuroscience Institute (BCNI) and Fraser Health Authority(FHA) in the domain of AI applied to clinical electroencephalographic (EEG) scans recorded and evaluated in the process of diagnostic workup in FHA’s public hospitals (n>40’000). The key goal of the SFU/FHA collaboration is to […]

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Targeted Incentive Offering for At-Risk Customers in an E-Commerce Setting

In this project, we focus on increasing sales in e-commerce shops by offering purchasing incentives to shoppers who are likely to leave without buying. More specifically, our goal is to predict which shoppers are likely to abandon their shopping cart and what can be done while they’re still on the site to customize their shopping […]

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Extracting 3D pose from video potentially using Neural ODEs

The project is self-contained. The goal of the project is to develop advanced AI assisted tools for artistic game development. It is anticipated that the advanced modeling of pose based on a mix of 3D motion capture (MOCAP) data and videos capturing human motion will help create advanced AI assisted game design tools that will […]

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Advanced Network Intrusion Detection Using Automated Algorithms and Threat Models

Computer attacks such as viruses, Trojans, etc. are a continuous problem for governments, companies, and individuals. The most common methods of detecting these computer problems like anti-virus systems rely on an attack being known and described before it can be detected. This opens a hole in computer security systems for new attacks that have not […]

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Software quality monitoring using AI/ML techniques

This project aims at employing AI and machine learning techniques to monitor and improve software quality. The quality of the system is to be measured by several metrics including the number of existing software defects, the normal/abnormal behavior of the system, test quality, test coverage, etc. The project focuses on studying historical data and trends […]

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3D spine imaging using tracked ultrasound and artificial intelligence

Obtaining accurate images of the spine is important for different medical purposes. For example, to measure how deformed the spine is in patients with scoliosis and select the most suitable treatment. Images can also be used to guide a clinician while inserting a needle to reach a exact location in the spine to administer anesthesia. […]

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Visualizing information in situ with 3D photorealistic environments

Advances in computer graphics and display technology have brought new opportunities to create stunning visual effects and interactive experiences. Industry concerned with data visualization is seeking to incorporate these advances into their visualization pipelines. For example, our industrial partner LlamaZOO Interactive Inc. attempts to present abstract data situated in 3D realistic scenes. However, most research […]

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Segmentation automatique de dents à partir des scans oraux

L’automatisation des tâches de fabrication dans les laboratoires de prothèses dentaires revêt un intérêt considérable, à la fois pour les techniciens et pour les patients. En effet, une partie importante du travail consiste en des tâches répétitives, longues et qui exigent un effort de concentration et de minutie soutenu. Par conséquent, il existe une grande […]

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Efficient Cutting for Haptic Surgery Simulation using Hybrid Deformation Models

This research project aims to expand Symgery’s line of surgical training products by simulating cutting and tearing of physical models in real-time. Cutting and tearing of simulated models typically requires additional computational overhead due to post-processing of the volumetric mesh. However, our approach will render the process to be more efficient by using a hybrid […]

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