Natural Language Processing for automatically checking novelty of ideas

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 […]

Read More
Developing rapid and portable detection technology for monitoring manganese in drinking water systems

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. […]

Read More
Foundational Models for Drug Discovery

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 […]

Read More
The Role of Public Participation in Identifying Stakeholder Synergies in Renewable Energy Project Development: the Case Study of Ontario, Canada

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 […]

Read More
Model-based Reinforcement Learning with Structured Representation

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 […]

Read More
Deep Learning Based Approaches to Synthetic Data Generation

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 […]

Read More
Build and improve image embedding models of cellular phenotypes

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 […]

Read More
Data and Visual Analytics for Prediction of Health Care Utilization Involving Musculoskeletal Disorders in BC

This study will establish the utilization rates of musculoskeletal services, for example, low-back pain, across healthcare systems in BC. To capture the utilization rates of musculoskeletal services, we can detect and establish the current frequency of these services related to the most recent healthcare expenditures. Knowing the utilization and expenditures would allow BC Chiropractor Association […]

Read More
Addressing the Discrimination experienced by Somali Canadians and Racialized LGBTQ Persons in Toronto

Addressing Racism in Toronto’’ is a one-year project to be conducted by Urban Alliance on Race Relations (UARR). The aim of this community-based research venture is to identify issues of access, equity and inclusion for two highly vulnerable and marginalized groups in Toronto: the Somali Canadian community and racialized LGBTQ persons who are homeless. Specifically, […]

Read More
Anatomical fiducials and their relevance to stereotactic neurosurgery: quality control and improving surgical targeting

Ultra-high field Magnetic Resonance Imaging (UHF-MRI) allows for visualization of deep brain regions in exquisite detail, unlike any other imaging modality. In Canada, there are only a few MRI machines that can generate magnetic fields strong enough (7T or higher) to obtain UHF-MRI scans. The ability to visualize and locate deeper brain regions with millimetric […]

Read More
Evaluation of novel antiviral compounds against SARS-CoV-2

SARS-CoV-2 appears to be poised to become endemic, meaning that we can expect continuous risk of exposure to infection. Despite highly effective vaccines, people still become infected, and some people become severely ill. Antivirals that can reduce symptoms and decrease the levels and duration of infection can aid in reducing onward transmission of the virus. […]

Read More