There is an exponential increase in the network traffic worldwide due to the growth of social networks, multimedia sharing web services, streaming of video-on-demand (VoD) contents. However, the bandwidth isn’t growing at the same rate as the demand, resulting in a loss of Quality of Service (QoS) and Quality of Experience (QoE) for the users. […]

Digitization of assets is becoming a dominant form of business operations today; the Internet of Things and increased connectedness to consumers and citizens alike is creating a decentralized virtual marketplace for digital services and assets. The potential for sharing technology assets is high due to digitization (the new way of referring to digital transformation). Principles […]

Internet of things (IoT) includes of multitude of sensors from a wide variety of applications. These sensors produce high volume and high velocity data. Recently there has been much interest in application of such technologies to improve energy management and agricultural practices. The sensors that are installed in the field transmit real time data regarding […]

Current research in semantic parsing suffers from lack of annotated data, which is hard to acquire. In this project, we aim at tackling the problem of converting natural language utterances to SQL language (Text-to-SQL) on complex databases in a low-resource environment. More specifically, we focus on the research of how multi-task learning (MTL) can help […]

Financial fraud is a serious issue that is taking place globally and causing considerable damage at great expense. Statistical analysis and machine learning tools can help financial institutions detect different types of fraud. In some cases however, mislabeling and the cost of classification may actually increase the volume of ‘false positives’ for supervised methods. As […]

This research will provide a prediction of sea conditions at a given location based on measurements from meteorlogic and oceanographic “smart” buoys in the general area. The motivation is to provide redundancy in the measurement of sea conditions for safe navigation within the Halifax Harbour when the main smart buoy in Halifax Harbour fails or […]

45 Drives—a Nova Scotia based company—offers a high-density, low-cost data storage solution called the Storinator. While this product has been very successful, clients have indicated they would like a clustered solution which offers similar performance and redundancy, without sacrificing security or drastically increasing the cost. Researchers at the University of New Brunswick have been identified […]

Machine learning (ML) has recently achieved impressive success in many applications. As ML starts to penetrate into safety-critical domains, security/robustness concerns on ML systems have received lots of attention lately. Very surprisingly, recent work has shown that current ML models are vulnerable to adversarial attacks, e.g. by perturbing the input slightly ML models can be […]

Machine learning algorithms are being used in a wide range of applications. It is a branch of computer science where the system can learn from the data and make decisions. Financial fraud is an increasing hazard in the financial industry, and it is important to detect a fraudulent transaction. Machine learning algorithms can be used […]

The project investigates how collaborative tasks can be enhanced in AR environments. The intern will develop three approaches to present shared information in a co-located AR setting and conduct usability studies comparing these approaches. The first approach will present information in the same location and same orientation to the collaborators, the second will present the […]

Fraudulent activities are hard to detect, but they cost financial institutions millions of dollars in monetary losses and legal costs every year. Millions of dollars are being lost in credit transactions as criminals are finding new, more sophisticated ways to conduct financial crime. This research project examines novel ways of detecting fraudulent behavior using powerful […]

With over 100,000 mobile health applications currently available and the volume of data collected using them, developing novel automated approaches to learn from biophysical large-scale data is critical. Wearables have become affordable; mobile devices are display-rich and the flow of information from sensors to mobile devices is sufficiently accessible for enthusiasts. A key question here […]