Modeling and forecasting the popularity of YouTube videos

Many YouTube content owners currently make money from their videos by allowing YouTube to display ads next to them. For these content owners, increasing the popularity of the video leads to more revenue, and therefore it is of great importance. The purpose of this project is to design an algorithm to predict the popularity of […]

Read More
Machine Learning Engineering and Optimization for Improving Seafood Production

In this project, machine learning and optimization will be applied to a 20 GB dataset on raw fish quality and process control parameters collected by the Tally software over a three-year period in a large industrial tuna cannery processor. The goal of the research is to design predictive machine learning and optimization algorithms maximizing the […]

Read More
Multi-sensor long-range object detection & classification under challenging perceptual conditions

Autonomous vehicles must be constantly aware of all aspects of the driving environment, and so are typically designed with both omni-directional and long-range forward sensor footprints. The ability to accurately detect, track and predict the motion of distant vehicles and pedestrians along the driving route remains a significant challenge, for today’s state of the art […]

Read More
Optimiser la résilience de la forêt urbaine

Le projet consiste à développer un système et une application web qui permettra aux aménagistes forestiers urbains de choisir la meilleure espèce d’arbre à planter à différents endroits de la ville afin de maximiser les retombées économiques et sociales et la résilience du couvert arboré face aux changements globaux. Nous développerons un système qui regroupera […]

Read More
Mobile Applications to Facilitate Physician-to-Physician Consultation

In the Nova Scotia healthcare system (and indeed across Canada), waitlists remain a major problem, particularly with regards to access to specialty care services. Virtual Hallway is a novel telehealth solution to this problem, providing an online platform which allows for rapid doctor-to-doctor communication with the goal of fast-tracking and improving patient care and reducing […]

Read More
Self-tuning servers within IBM cloud

Modern cloud-based applications are deployed as isolated processes in containers or virtual machines. These applications frequently require tuning by the application developer (or a DevOps engineer) in order to extract the requisite performance. For example, a Java application executing within a Docker container may have radically better performance if the host JVM runs with a […]

Read More
Design Analytics and Design Reporting Tools

Design data is broadened beyond specifying built-environments to support evidence-based decision-making in the early phases of design. For using data, designers usually rely on specialized data visualizations. There is a need for interfaces specifically tailored for reporting designs with their form and performance data to and for seeking feedback from the other stakeholders who are […]

Read More
Advanced Recommender Systems for Ecommerce

Numerous studies have recently proposed and highlighted novel techniques for recommendation, motivating the project of building the next generation of recommender systems for ecommerce platforms. This proposal aims at experimenting with one high-potential technique for modelling the recommendation problem, that makes great usage of the complexity of ecommerce data: Graph Neural Networks (GNNs). GNNs are […]

Read More
Can deep learning algorithms be trained to automate the classification of information held in historical and repeat photographs?

Repeat photography is a valuable tool for evaluating long-term ecological change. Historical photographs used for repeat photography often predate conventional remote sensing data by decades, and the oblique perspective of the photographs capture details of the landscape absent in nadir imagery. To date, most approaches to quantifying landscape change using repeat photography have involved manual […]

Read More