what we are working on


The Canadian Centre for Computational Genomics (C3G) is a geographically distributed innovation program that provides bioinformatics analysis and high-performance computing services for the life science research community across Canada. Toronto node consists of team members from UHN and SickKids, and the Montreal node is based at McGill University.


Care4Rare is a large pan-Canadian collaborative network of clinicians, bioinformaticians, scientists, and researchers focused on improving the care of rare disease patients in Canada and around the world. Care4Rare includes over 20 academic sites across the country and is recognized internationally as a pioneer in genomics and personalized medicine.


COVID gap is a contact tracing application that uses Wi-Fi signals to help identify staff in proximity to other staff members. It uses data collected from mobile apps, access points in the building, and IoT devices to build models for predicting distances between two devices. This application can be used to identify locations at UHN where individuals congregate, and users who were within the distance threshold of a COVID-19 patient.


The UHN Ted Rogers Centre for Heart Research (TRCHR), the Peter Munk Cardiac Centre (PMCC) and UHN Digital are collaborating to build the Digital Cardiac Health Platform (DCHP), a secure data integration platform for secondary use of clinical data. The DCHP will facilitate UHN data integration across the various isolated silos and will enable quality improvement initiatives.


Genomics4RD is an initiative of the Care4Rare Canada Consortium. It is the first Canada-wide data lake for rare disease research, providing a centralized repository of structured and unstructured data from 5,000+ participants. 


The Health AI Data Analytics Platform (HAIDAP) is a collaboration between HPC4Health, ICES and Vector with support from Compute Ontario to create a secure, regulatory-compliant research computing environment in which AI and machine learning techniques can be used and ultimately creating a unique, world-class AI data platform.


The development, testing and improvement of PhenoPad — an AI-based clinical tool enables the digitization of highly structured patient data and facilitates patient interaction while providing physicians with enough freedom to perform their jobs efficiently.