Visual-haptic Representation for Zero-shot Learning

Humans recognise objects in the world leveraging multi-modal sensory inputs beyond visual aspects (images and videos). Touch based information (Haptics) possesses rich information about structure, shape and other objetness properties. In this work, we will study and learn cross-modal representations between vision and touch. To connect vision and touch, we plan to introduce a zero shot classification task of recognising unseen object categories from shapenet dataset using haptics signals.

Monitoring of turbine runner blade strains from indirect measurements using AI

Hydro-Québec has data acquisition systems for a multitude of sensors, some of which have been installed since almost 20 years in its electrical generation equipment (turbine-generator units - TGU). The collected data is primarily used to ensure that the information is adequate in the event of an equipment breakdown or for specific behavioral studies.

Short term Electrical Load Forecasting

Load forecasting is an essential activity for a company like Hydro-Québec. It is necessary for objectives as varied as the management of production or the management and maintenance of the electricity network. Any significant forecasting error can result in reliability issues, loss of opportunity, or additional costs to the business. On the other hand, a good prediction would allow Hydro-Québec to generate additional sales in neighbouring markets. With the deployment of its Advanced Measurement Infrastructure (AMI), Hydro-Québec now has a significant amount of new consumption data.

Solar Radiation Forecasting

The main duty of Hydro-Quebec is to respond efficiently to the energy demands of customers, in a safe way while remaining competitive in the markets as well. In a changing energy context, the production of solar photovoltaic energy represents a new challenge for Hydro-Quebec, which will have to integrate and to balance this intermittent resource to guarantee the reliability of the electricity grid.

A smart edge computing infrastructure to support workflows, communication and logistic in COVID-19 healthcare facilities

The ability of the health system to manage a massive influx of patients is based on the combination of four factors: the personnel, the equipment, the physical spaces and the system in place. A combination better known in jargon as the 4 "S" (staff, stuff, structure / space, system). A fifth factor that is often misunderstood is synchronicity.

Power network transfer capability (Phase II – data error detection)

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 maximize energy exports. The transfer limit is now conservatively estimated based on a certain combination of simulated network configurations.

Active learning for visual detection on inspection robots

Robotics vehicles deployed at Hydro-Québec up to now are still mainly manually operated and human intervention is continuously required. The project aims to equip Hydro-Québec's current and future fleet of inspection robots with autonomous inspection capabilities. The intern will leverage breakthroughs in artificial intelligence to enable robotic vehicles to realize real-time automated visual inspection of the company's infrastructure and use a simply and securely deployable robotic vehicle to perform the company’s first fully autonomous power line components inspection mission.

New molecular representation, molecular generation, and data mining strategies for thedesign of SARS-CoV-2 therapies

The goal of the project is to facilitate the research and development of new drugs using machine learning. More specifically, exploring new techniques to model molecules and how they can be represented. Doing so will involve training deep learning models on multiple small datasets with the objective of improving the generalization performance on new tasks. The trained models will have to be accurate even in the context of new types of molecules. With the small amount of data available, out-of-distribution techniques will be used.

Automated Pilot Performance Assessment

In a trend towards increasingly complex aircraft, tomorrow’s pilots must possess excellent situational awareness, problem solving, leadership and communication skills. Pilots trained for these competencies will be best equipped to handle unforeseen situations safely. In this project at Paladin AI, intern will focus on working with real flight simulator data that has been labeled by human experts. Intern will work with this data to develop new analytics techniques for inferring pilot competency. The intern will identify one or multiple markers of either good or poor pilot performance.

Predicting demand and inventory shortages for better inventory management in health care institutions

This project aims to predict demand and inventory shortages for better inventory management in health care institutions. This will initially allow for a reduction in the expenses generated by emergency orders placed during a stock shortage. Indeed, it will be possible for the establishment to order a larger quantity of the product from the supplier or to place an order with another supplier.