The research project, guided by Professor Stephen Smith, focuses on addressing environmental challenges related to water pollution and debris detection in the water areas, with a specific emphasis on garbage and waste detection on the water surface. The project entails a systematic literature review and analysis of various computer vision models to detect and classify […]

Machine learning attempts to model high-level abstractions in data using multiple processing layers with complex structures or non-linear transformations. Federated learning is a distributed machine learning approach that allows multiple parties to collaborate on training while preserving user data privacy. However, the data from each party is typically non-independent and identically distributed (Non-IID), which can […]

Machine Learning (ML) approaches generally consist of training an algorithm on a given dataset containing data which has to be analyzed or otherwise understood. For an ML application to be successful, careful thought must be given to ensuring that the architecture of the algorithm chosen is fit for the task at hand: some architectures are […]

The project aims to develop a state-of-the-art numerical simulator to compute transistor’s physical behaviors at deep cryogenic temperatures. First of its kind, the simulator will incorporate physical effects critical for transistor’s operations at cryogenic temperature such as inelastic scattering, while maintaining computational efficiency and robustness. The successful outcome will provide the research community a widely […]

Japan is a leading example of a nation with a rapidly ageing society and currently consists of the highest proportion of elderly adults worldwide. Among others, this has led to a series of downstream concerns, including labour shortage issues and reduced ability of working individuals to finance those who are retired. As one of the […]

Monocular depth estimation aims to infer the distance information of objects in a 2D image. It is an integral part of many computer vision tasks and has applications to autonomous driving, robotics, and virtual reality, among others. This project focuses on developing a new deep-learning-based monocular depth estimation method with high efficiency, competitive performance, and […]

The main goal of her study is to make sustainable polymers from lignin that can be used in three dimensional (3D) printing material production. The student will work on making 3D printing materials from polymerized lignin and polycaprolactone (PCL). At Abo Akademi, the student will use different monomers to generate composites of lignin and PCL. […]

The overall objective of this study is to generate lignin-derived sustainable emulsion systems for coating applications. The main focus of this study is on the generation of functional lignin derivatives and then the conversion of these lignin derivatives to lignin nanoparticles. Afterward, the use of lignin nanoparticles in oil-water emulsions will be studied for coating […]

The demand for eCommerce and online orders has risen rapidly in recent years, this drives the need for highly efficient and automated item sortation systems. Kindred AI is a technology company with the objective to bring artificial intelligence and robotic technologies into the workforce of eCommerce, parcel and order fulfillment. As a part of the […]

We propose a solution to achieve a strong interfacial connection between FFF-printed materials and SLA-printed materials by utilizing an ester exchange reaction. Common FFF materials such as PETG and PLA contain an ester structure that can undergo ester exchange reactions with other alcohols in the presence of a strong base such as Triazabicyclodecene (TBD) and […]

There has been a lot of effort in making printed media accessible to low vision or blind individuals. Braille has been extensively utilized to make text accessible to the blind. Software that automatically converts text to speech has also been employed for this. However, the existing solutions are not adequate for conveying graphical information to […]

Road safety affects everyone, not just Geotab customers. With several years of driving and environmental data from over 2 million connected vehicles we have an opportunity to make our customers safer, as well as our communities and cities. In an effort to reduce accidents, we need to understand both the driving behavioural patterns that are […]