Hololabs Studio Inc. is developing a mobile platform called Diyorama, which enables users to arrange images into interactive 3-~ scenes with an aesthetic similar to paper craft and collage art. Users can include images from their photo libraries, social networks, or image search results in order to create customized playable scenes from existing content. The […]

Deep neural network (DNN) is a class of machine learning algorithms which is inspired by biological neural networks. Learning with deep neural networks has enjoyed huge empirical success in recent years across a wide variety of tasks. Lately many researchers in machine learning society have become interested in the generalization mystery: why do overparameterized DNN […]

Municipalities are seeking ways to reduce the effects of uncontrolled rainwater and one of the primary contributors to the problem is residential downspouts. Downspout disconnections and redirections are low-cost ways to reduce the overall imperviousness of urban and suburban landscapes and ameliorate stormwater issues. This project will use machine learning to analyze Google street view […]

This project intends to research the building of scalable, low-cost and robust alternatives andimprovements to existing systems for mineral sensing and sorting in order to achieve greaterproductivity and efficiency by means of improving speed and accuracy in the process of miningminerals from low grade rocks. The project will combine developments in embedded and streamingsystems, parallel […]

RVezy is a technology company that brings explorers and RV Owners together: Think Airbnb for RV’s. This project will involve two main components, both driven by AI and analytic solutions: 1) Search Optimization: Improving RVezy’s search algorithm to better tailor their customer experiences. 2) Marketing Spend Ratio: Integrating shallow machine learning models to improve return-on-marketing-investment. […]

SkipTheDepot is a door-to-door bottle collection service based in Calgary which allows users in Calgary and Edmonton areas to request bottle recycling pickups, and the COVID 19 pandemic has caused demand for these services to increase. In order to meet rising demand, it is important to develop a clear understanding of how the service is […]

This project will build on the work previously completed in the MITACS project done by Dr. Michael Bauer, Omid Mola and Cyborg Trading Systems (CTS) – Integration of an Autonomous Trading Platform. The previous project formed the foundation of developing an autonomic system in an algorithmic trading application. The initial project was successful in determining […]

Le projet en question est de type Design Science. Il éclot dans un contexte d’expansion où le système d’information (SI) de l’entreprise expose ses limites. Plus spécifiquement, son caractère manuscrit lui proscrit coordination et automatisation : coordination car l’information demeure figée sur feuille et donc inaccessible à des parties éloignées; automatisation, dans la mesure où […]

Materials with different sizes, shapes, or materials come into the process every day, they need to be sorted, placed, and usually fed into a machine for processing. Traditionally, this task is very hard to be automated because of the non-fixed position of the part and frequent part changes. For this random bin picking project, we […]

As online educational platforms and blogs such as Coursera, Edublog, Korbit Technologies Inc. etc. are becoming increasingly popular, a great way for students to learn is to solve QA problems on educational texts. Students also learn by getting answers to their questions. Since manual QA generation of huge content of educational texts seems impracticable, an […]

To improve traveller services in train stations, SNCF and Keolis Canada seek to develop a mobile application for real-time geo-localisation based on still images captured by the user on its smartphone. This would allow guidance through the station and provide key information. This project will develop a Deep Learning (DL) model for accurate and real-time […]

Financial data are known to be generated from complex distributions, often assumed to be changing over time. The aim of this project is to build a simulator of multivariate time series, parameterized as simply as possible by a user, with the freedom to build different models, to assess their general behavior and key properties. This […]