Anatomical consistency and confidence estimation of cardiac segmentation of ultrasound images using variational auto-encoders

Artificial intelligence shows great promise in the field of medicine. Indeed, neural networks can learn to perform many tasks that would otherwise take hours for physicians to accomplish. For example, neural networks can learn to classify each pixel in cardiac echography images with respect to the anatomical region (cardiac echography segmentation). This allows for faster diagnostic of various pathologies. However, neural networks are not infallible, and it is not trivial to identify these failure cases without expert intervention.

Market making for digital assets

Market makers facilitate trading in electronic financial markets by simultaneously offering to buy and sell the same asset at any given time. Their role is to provide price stability and increase market liquidity to improve its overall efficiency. Digital assets markets are extremely fragmented and present both challenges and opportunities for market makers. These latter must offer participants accurate prices while balancing their asset inventory on many venues at the same time, what represents a difficult synchronization task.

Développement de jeux pédagogiques dans une plate-forme d’apprentissage en ligne autonome

Le projet consiste à développer des jeux pédagogiques visant l’enseignement de la programmation à des apprenants de 10 ans et plus. Les jeux doivent rapporter les erreurs de façon claire et précise, dans un niveau de langue approprié à des débutants, ainsi qu’effectuer de riches animations, dessin 2D et effets visuels afin de pouvoir capter et maintenir l’attention des apprenants en bas âge. Une attention particulière doit être portée aux erreurs rapportées, afin qu’elles soient faciles à comprendre par l’apprenant et qu’elles promeuvent un environnement pédagogique autonome.

Intelligence artificielle pour le prétraitement des données chez Co-operators

L’historique des données que possède une entreprise d’assurance telle que Co-operators concernant leurs clients, les soumissions, les réclamations, etc., constituent un élément stratégique clé qui est au coeur du développement des affaires. La capacité de l’entreprise à utiliser, à manipuler et à interpréter ces données constitue un élément fondamental. Le prétraitement de ces données est l'une des étapes les plus longue du processus d'analyse des données.

Advanced Free-space Optical Link Prototype for Space Applications

As we advanced into the information age, the need for high capacity communication channels is becoming
ubiquitous. As the next generation of satellites is being deployed there is a need for efficient interconnections
between them, especially for those forming low earth orbiting constellations for the coming Internet-of-Space
applications. The limited radio frequency spectrum available is not sufficient to implement these communication
links, and thus, free-space optical interconnects (FSOIs) are expected to become the technology of choice to
interconnect satellites.

Towards a design for an inclusive conversational agent adapted to autism and language difficulties

This project aims at developing a conversational agent for autistic people and their families, based on highly accurate training datasets while deploying Natural Language Processing (NLP) and Deep Learning (DL) techniques. This project will help promote inclusion and diversity into AI design by using the right data to train the conversational agent system to be inclusive, while taking into consideration gender roles, age, diversity and social and ethical problems. This could eventually result in a more diverse and inclusive world.

Optimization of task sequencing and allocation

Nowadays, software projects are no longer isolated but drive the business process of many non-IT companies. With the rise of AI applied in many industries, the problem of optimally scheduling tasks and allocating proper resources has significantly increased the challenge because of the diversity of tasks and stakeholders in the project. Due to the large volume and dynamic nature of the required information, manual optimization is typically error-prone and inefficient.

Développement d’un robot autonome pour le sarclage automatique du bleuet sauvage

Avec les progrès prodigieux des dernières années en matière d’agriculture de précision, ce projet apporte une solution originale à la problématique de la détection automatique des mauvaises herbes ainsi que leur éradication dans les bleuetières de bleuets nains (sauvages). Le principal objectif de ce projet consiste à développer un système robotisé autonome capable d’effectuer la détection automatique de mauvaises herbes permettant ainsi de cibler plus précisément les zones infestées au sol et ainsi orienter en 3D les opérations phytosanitaires de sarclage.

Providing value to SMB by optimizing ETL

New point-of-sale (POS) machines help small businesses catalog transactions and inventory by warehousing customer, vendor, product, and sales data. This data, however, is usually warehoused in a data table that is not accessible to modern analytics and management software, such as Lightspeed. To help these businesses take advantage of their data, Enkidoo provides a service to export small business data by building an extract-transform-load (ETL) pipeline to Lightspeed. However, this process can be tedious, due to mismatches in column data and the template.

Unsupervised Anomaly Detection in multivariate Time Series Data

The enormous amount of data generated can be exploited using state-of-the-art AI algorithms to drive business decisions. However, a significant drawback of existing approaches is that the algorithms require a considerable amount of human effort and energy to prepare and annotate the data. Recent advances in deep learning and AI propose to solve this bottleneck using a paradigm referred to as 'Unsupervised' algorithms.