Today’s marketplace is moving faster than ever, and companies are challenged to distribute their products more quickly, efficiently and cost-effectively. This has led to the rise of cross-docking in the global supply chain to help keep pace with customer demand. Cross-docking refers to the practice of unloading goods or materials from an incoming vehicle (e.g., […]

Today’s marketplace is moving faster than ever, and companies are challenged to distribute their products more quickly, efficiently and cost-effectively. This has led to the rise of cross-docking in the global supply chain to help keep pace with customer demand. Cross-docking refers to the practice of unloading goods or materials from an incoming vehicle (e.g., […]

Liquefaction is a destructive phenomenon which usually takes place after an earthquake in areas with water-saturated soil or sand. During the liquefaction process, soil loses its strength and can no longer support structures and buildings which often leads to their destruction. To prevent damages associated with liquefaction, it is critical to study this phenomenon and […]

The Alberta Biodiversity Monitoring Institute (ABMI) monitors biodiversity across Alberta. ABMI has developed an application called NatureLynx to facilitate the collection of natural history observations by broad stakeholders, including the public. This application will enable people who are not professional scientists to participate in the process of collecting data; this is called citizen science. Initially, […]

This project will focus on furthering the development of a compact picosecond infrared laser (PIRL) system for use in surgical applications. This laser system, which represents a new paradigm for laser surgery, is unique in its ability to provide high-speed cutting of biological tissue without the collateral damage to surrounding tissues inherent in current surgical […]

Dizziness is among the top three reasons that patients seek medical attention, and one of the most common disabling conditions that humans face. One of the diseases that may cause dizziness is Meniere’s disease, which its correct and timely diagnosis and separation from other causes of dizziness with current techniques are quite challenging. On the […]

While we enjoy the modern convenience brought by a multitude of man-made organic chemicals, such as surfactants and flame retardants, the exposure to these compounds, some of which are bio-accumulative, persistent and even toxic, may endanger our health. Humans are exposed to chemicals in consumer products during both product use in the indoor environment (near-field […]

Thousands of organic chemicals have been synthesized and commercialized for industrial and consumer uses. However, an increasing number of organic chemicals are revealed to be “hazardous” because of their potential adverse environmental and/or health effects. The project seeks to identify the primary route(s) that humans take up these organic substances, e.g., use of personal care […]

Graphics Processing Units (GPUs) are increasingly used to accelerate applications and to reduce their energy use. GPUs are particularly attractive for mobile platforms, where battery life is important. However, GPUs are hard to use, requiring developers to apply optimizations to their code to realize the performance and energy benefits of GPUs–a tedious and error prone […]

The fellowship mainly investigates an analysis of the state-of-the-art approaches, design and implementation of cutting-edge deep neural network models to be used on a mobile platform. It explored ways to optimize the deployment of these machine-learning models for prediction tasks on the mobile devices which requires energy efficiency and accuracy.

Rapidly increasing amounts of mass spectrometry (MS) data pose new opportunities as well as challenges to existing analysis methods. Novel computational approaches are needed to take advantage of latest breakthroughs in high-performance computing for the large-scale analysis of big data from MS-based proteomics. In this project, we aim to develop new applications of deep learning […]

As a result of recent advances in high-throughput technologies, rapidly increasing amounts of mass spectrometry (MS) data pose new opportunities as well as challenges to existing analysis methods. Novel computational approaches are needed to take advantage of latest breakthroughs in high-performance computing for the large-scale analysis of big data from MS-based proteomics. In this project, […]