Development of Conversational Agents and Applications in Playful Environments

In this project, we propose an intelligent conversational agents prototype that provides meaningful, playful exchanges in different interactive settings. By taking advantage of the latest advances in artificial intelligence (AI) and creating a model founded on knowledge from social and cognitive sciences, we will build a series of digital avatars to test their interaction ability. This research-creation project connects to other disciplines like Human Computer Interactions (HCI).

Complementary and competitive interactions between wild and managed bees - Year two

A diversity of native bee species inhabit agricultural and urban landscapes and can be more effective pollinators than the widely employed European honey bee. However, honey and wild bee communities often overlap, which means these bees compete for the same floral resources. Studies of competition between wild and managed pollinators are limited due to methodological constraints. This restricts our ability to predict how pollination and bee diversity will be affected by changes in pollinator community composition.

Development of an efficient coding for CDMA-based passive RFID tags

Radio frequency identification (RFID) is a technology that uses radio frequency to identify and track tags attached to objects. This technology is employed in different industries such as asset tracking, supply chain management, ID badging, etc. Current solutions for object tracking have limited precision, suffer from low performance, and are expensive and complex. In this project, by implementing a technology called code division multiple access (CDMA), we improve the RFID system performance significantly.

Finding position and characterization of the defects in 3D point cloud

The inspection process has been an inseparable part of manufacturing to measure dimensions such as diameter, flatness, roundness and straightness of the parts. Besides, on some machined surfaces, it is required to measure roughness and identify surface defects. For defect detection, companies are still relying on visual inspection, which is very slow and labor-intensive. To overcome all challenges, interferometry instruments are used to acquire 3D images. Still, once a surface is acquired, the position and size of defects have to be found, and sometimes defect has to be classified.

Organic cathode materials for alkali-ion batteries

Clean renewal energy sources, such as hydro, wind, and solar energies, have been receiving increasing demands for sustainable societal developments. Due to their intermittent nature, rechargeable batteries are required for the storage of these renewal energy sources. Current rechargeable batteries constructed with conventional inorganic cathode materials have restricted energy densities, along with sustainability issues.

Advanced AI for Demand Forecast, Assortment Planning and Plan Monitoring in Fashion and Apparel Retailing

Retailers require reliable demand forecasts for their operations management and planning. Demand forecasting for fashion products is, however, an extremely challenging task. A good solution for this problem should address at least the following three questions: (i) high volatility of demand and its dependence on external factors (ii) forecasting flexibility for different spatio-tempo-hierarchical aggregation levels, and (iii) forecasting for new products without historical data.

Detection of Human Presence/Activity through Radio Frequency Signals with Artificial Intelligence

The goal of this porject is to develop a prototype system for human presence/activity detection through radio frequency signals. There have een some recent promising results reported in the literature regarding such detections through WiFi signals using artificial intelligence-based approaches. The postdoc will focus on reproducing earlier results, then move on to enhance the system to detect some human activities of interest. The partner company would like to design, build and commercialize a line of products based on the developed prototype.

Similarity detection on female pelvic anatomy imaging data usingMachine Learning methods and develop a first version of a measuringdevice prototype

Pelvic Organ Prolapse (POP) is a condition 1 in every 10 women is diagnosed with. The current non-surgical treatment for POP is an intravaginal device called pessary which has a 40% failure rate as its shape is not fitted to the female anatomy. Poor pessary design and performance arises from the limited data that is studied on the pelvic anatomy. The current research project will study available imaging data using Machine Learning algorithms to facilitate and automate the process for assessing and treating POP.

Understanding and designing the female pelvic anatomy, a measuring device and an intravaginal device using 3-dimensional modeling techniques and Artificial Intelligence

Pelvic Organ Prolapse (POP) is a condition 1 in every 10 women is diagnosed with. The current non-surgical treatment for POP is an intravaginal device called pessary which has a 40% failure rate as its shape is not fitted to the female anatomy. Poor pessary design and performance arises from the limited data that is studied on the pelvic anatomy. The current research project will study available imaging data using Machine Learning algorithms to facilitate and automate the process for assessing and treating POP.

Development of antiviral surfaces to mitigate the transmission of COVID-19

In March 2020, the new human coronavirus disease COVID-19 was declared a pandemic. As of May 21, 2020, the World Health Organization has reported over 4.8 million confirmed cases, including over 323,000 deaths worldwide. Only in Canada, the number of confirmed infections and deaths have reached over 80,000 and 6,000, respectively. Apart from the elevated rates of death and illness, this pandemic has caused major social and economic disruption throughout the world.

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