The project aims to facilitate the research and development of new drugs by exploring Machine Learning methodology useful for both the generation of new molecules and the prediction of molecule properties. Doing so will involve training deep learning models on a large number of small, heterogeneous datasets, with the objective of transferring learned representations quickly […]

Brain MRI scans are a critical component in the diagnosis of neurodegenerative disorders. However, there is a wide diversity in terms of the image quality and resolution obtained from different MRI scanner. In particular, it is common to find coarse resolution MRI scans (e.g. every axial slice is 3-5 mm thick), which limit the type […]

Machine-transcription of speech into text is very helpful in many scenarios. Consider the case of machine-transcription of conversation between a Doctor and a patient. If we are able partition and identify the segments of patient’s speech from those of doctor’s, then the transcribed text is more structured and can be more helpful for further use. […]

In this project, we propose to expand support of SOTI’s MobiControl (MC) to Tizen Operating System. SOTI MobiControl has assisted numerous enterprises to overcome the management issues due to lack of security and improve business performance by monitoring the health and safety of employees, and increasing productivity, with the introduction of wearables and other IoT […]

By virtualizing all the various appliances in the network, Virtual Network Functions (VNF) became a key enabler for the coming 5G infrastructure and nowadays a major shift is under way bringing an evolution to cloud-native VNF. In the latter operational model, applications are decomposed into microservices running inside containers to enable automated installation, configuration and […]

The main duty of Hydro-Québec is to repond efficiently to the energy demand of customers, in a safe and secure way while remaining competitive in the markets as well. The main goal of this start-up project is to support Hydro-Québec in developing a future-oriented energy system by proposing innovative technical solutions. Among these solutions, deep […]

Hydro-Québec is a public utility that generates and distributes electricity. Despite selling most of its electricity in Québec, its most lucrative sales are in the neighboring markets. To ensure the best possible quality of service, the transmission system must remain stable, but to maximize profits, the company also wants to increase its transmission capacity to […]

ClosedLoop.ai is an AI-based predictive analytics platform that goes beyond traditional claims-based risk scores to use all patient-related healthcare data to provide both clinicians and care managers with a full breadth of timely, transparent and accurate predictions of health outcomes. ClosedLoop.ai helps value-based providers confidently answer a variety of health-care questions like, which patients are […]

The company Lexum is an undisputed leader in the development of information retrieval tools for the law – statutes, regulations and decisions of courts and tribunals. The project is to improve a new tool offer by the company. The tool is used to retrieve a list of legal subjects from a factual description. With that […]

This work aims to explore software and hardware co-optimization for deep neural network (DNN) inference applications. Once a model is trained to sufficient accuracy, the model is used to make inference or predictions based on this trained model. With increasing performance, more people are using these models for tasks such as translation, self-driving cars and […]

The task of sentence simplification can present itself in multiple forms. It could consist in correcting the punctuation of a sentence like so: Avant : J’ai acheté un bateau je l’aime beaucoup. Après : J’ai acheté un bateau. Je l’aime beaucoup. However, a sentence can be both long and written correctly. In this case, it […]

The proposed research is a collaboration between Persistant Studios’ PopcornFX and SFU’s iVizLab to collaboratively work on ways to understand the processes involved in content creation using a real-time particle system. The iVizLab’s research focuses on using real-time visuals with the biodata from the users as one of the main interfaces to create affective systems […]