Design and Analysis of Picocells in Wireless Cellular Networks

Future wireless networks demands ubiquitous coverage and higher data rates at low infrastructure cost. The novel network deployment where macro base-stations overlaid with low power nodes referred as picocell is the most promising solution towards this goal. The proposed research project intends to evaluate the system-level performance of the picocell wireless network. To quantify the […]

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Development of a High Power Picosecond Infrared Laser for Medical Applications

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 […]

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Integrated Far- and Near-Field Human Exposure Modelling for Organic Substances

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 […]

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Integrated Far- and Near-Field Human Exposure Modelling for Organic Substances – Year two

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 […]

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Using Deep Learning for Auto-tuning of High Performance GPU Applications

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 […]

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Using Deep Learning to Auto-tune GPU Application

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.

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Zero-Emission Public Transit Fleet Systems

Electrification of transit vehicles is a part of Ontario’s long-term strategy to reduce transportation-related greenhouse gas (GHG) emissions. However, transit agencies and utility/local distribution companies face significant technological and operational hurdles in integrating “off the shelf” electric bus technologies. The postdoctoral fellow collaborating with Canadian Urban Transit Research & Innovation Consortium will work with transit […]

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