These are challenging times for healthcare leaders. Since the pandemic, it has become abundantly clear that healthcare is at a tipping point. With burnout, retirements, and resignations, healthcare leadership positions are now more available than ever. CHLNet and LEADs Change have studied leadership during COVID-19 and have highlighted the demands on leadership and the need […]

Sleep is crucial for the formation of novel memories, and it underpins much of our psychological well-being. Unfortunately, millions of Canadians suffer from sleep difficulties, which are especially prevalent among women and populations with low education and income. These difficulties result in poorer cognitive performance and reduced well-being. Finding solutions to these difficulties is often […]

The purpose of this project is to make use of the AI algorithms to enhance the energy consumption related to indoor heating ventilation and air conditioning (HVAC). The project involves collecting data using wireless sensors network, developing thermal dynamic model of a building, and developing Model predictive control (MPC) solver that reduced the energy consumption. […]

A new load-bearing precast concrete wall panel system has been proposed that uses composite materials instead of steel for reinforcement to reduce the level of heat loss through them and increase their R-Value. The panels will undergo destructive structural testing to determine how well the composite material system compares to a similar wall design that […]

Temporary disruptions in the pedestrian environment, such as construction or snow, make it difficult for people with disabilities (PWDs) to reach destinations in their community. Cities struggle to communicate alternate routes that are accessible to everyone when these disruptions occur. Grounded in a context of data valorization and transfer for the development of smart and […]

XLScout uses Natural Language Processing (NLP), Machine Learning (ML), and Innovation/Scientific principles to deliver actionable intelligence and accelerate innovation by analyzing large patent and research databases. The company is eliminating the pain of manually going through document and quickly providing relevant information to support data-driven strategic decisions. Presently XLScout hosts a data vault of over […]

Manganese (Mn) is a contaminant of emerging concern in drinking water as a growing body of epidemiological evidence has identified adverse cognitive, neurodevelopmental and behaviour effects in children. Canada has been a global leader in advancing the regulatory framework for Mn in drinking water, and in 2019, Health Canada published a new drinking water guideline. […]

A foundation model (FM) is any model that is trained at scale on a broad dataset and can be adapted (e.g., fine-tuned) to a wide range of downstream tasks; current examples include BERT, CLIP and GPT-3. In this project, we investigate the challenges of building foundational models for drug discovery: capturing multi-modal information, explainability, and […]

Over the past several decades, the scope of decision-making in the public domain has changed from a focus on unilateral regulatory verdicts to a more comprehensive process that engages all stakeholders. Consequently, there has been a distinct increase in public participation in the environmental decision-making process. While the potential benefits of public engagement are substantial […]

Recent advancements in deep reinforcement learning (RL) have enabled incredible breakthroughs on a wide variety of problems in which computer systems are required to learn through interacting with the environment with no or minimal human intervention. An example of this is DeepMind’s AlphaGo agent, which taught itself to play Go at a superhuman performance. Deep […]

Synthetic population generation is the process of combining multiple socioeonomic and demographic datasets from various sources and at different granularity, and downscaling them to an individual level. Although it is a fundamental step for many data science tasks, an efficient and standard framework is absent. In this project, we propose a multi-stage framework called SynC […]

The over-arching goal of the project is to explore the use of several recently developed self-supervised image representation learning methods in an attempt to improve performance across several biologically relevant benchmarking tasks at Recursion. At recursion, deep-learning based models are used to generate feature embeddings for our imaging data and these embeddings to generate downstream […]