Goal-Conditioned Reinforcement Learning

The goal of the project is to improve upon the methodology behind goal conditioned learning. In this framework, similar to the setup in traditional reinforcement learning, an agent interacts with an environment. However, instead of training the agent to maximize return, the agent is trained to reach a given goal at the end of the […]

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Learning Discussion Thread Representations to Empower Content-based Recommendation

VerticalScope is a company that owns online forums in many domains, such as automotive, health, technology, and powersports. VerticalScope uses a content based recommender system to mitigate the cold start problem, where a large portion of traffic on the forums are made by unregistered users. The goal of this project is to learn representations of […]

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Designing ‘Zero credit touch’ (ZCT) pre-approved credit underwriting program for retail customers

ICICI Bank has developed various ‘Zero credit touch’ (ZCT) strategies where without any credit intervention and additional information taken from customers, credit facilities can be provided. But there are several challenges in the expansion of ZCT strategies, namely, (i) current credit models which are a combination of business rules, scorecards and machine learning models, do […]

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Multilingual B2B Supplier Detection and Information Extraction

At Tealbook, we search the web to make the world’s business-to-business supplier websites readily accessible. We extract important sentences and keywords to create a searchable database that buyers can then use to find the right supplier for their needs. But right now, we are limited to servicing English-language organizations. Can we expand our services to […]

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Investigating strategies for optimizing immunity to COVID-19: examining the impact of probiotic lactic acid bacteria-derived secretomes on epithelial cell and macrophage immune activity

Strategies to promote immune defences against COVID-19 infection are urgently needed. The gastrointestinal tract is a potentially important route for COVID-19 infection and for generating protective anti-viral immunity against this pathogen. Certain features of COVID-19 contribute to its ability to evade and subvert our immune defences. Type I interferon is a key immune protein that […]

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iStandardize: Recommendations for Healthcare Form Standardiz

iStandardize is an AI-powered machine learning solution that is designed to streamline the standardization of clinical order sets (i.e., forms) by using machine learning and natural language processing techniques. Currently, hospital networks use multiple versions of forms and order sets, many of them are similar in nature. The lack of standardization poses a challenge in […]

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Monitoring the sustainability of agricultural system for Ontario’s Greenbelt

This project aims at developing information and knowledge that will promote public and policy support for the long-term sustainability of the agricultural system surrounding the greenbelt. Based on a preliminary research led by the Friends of Greenbelt Foundation, this research will develop a monitoring framework for the viability and protection of the agricultural system in […]

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Technologies for Improved Sustainability of Long-Life Flexible Pavements

A sustainable pavement is one that is safe, smooth, efficient, economic, and environment friendly, meeting the needs of present-day users without comprising those of future generations. Sustainable flexible (asphalt) pavements, in particular, are those that minimize environmental impacts through the reduction of fuel and energy-based materials (asphalt cement, for example) consumption, more effective use of […]

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Described Video and Language Detection on Audio-tracks Using Machine Learning

Bell Media receives content from different providers, including content it produces in-house. There are standards for tagging audio tracks with metadata however many facilities (including Bell) do not adhere to these standards. Currently Bell uses a manual approach to classify unlabeled audio tracks, which is inefficient, and time consuming for massive digital media that Bell […]

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Interpretable Machine Learning for Predictive Analytics in Employee Benefits Insurance

In recent years, many machine learning methods have been developed for predictive analytics and automated decision making. However, the lack of explanation resulted in both practical and ethical issues. In this project, we will employ and advance interpretable machine learning methods for various predictive analytics tasks in employee benefit insurance. The proposed methods can be […]

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