CiDrep SickKids Research Accelerator

Biomedical Informatics in Medicine for Sick Kids

Our scientific research supports our mission and strategy through fundamental scientific studies and explorations in artificial intelligence, machine learning theory and across the domains of informatics applications to decipher human disease heterogeneity.

BMI and AI Medical Research

Biomedical Informatics

We develop "AI" supervised and unsupervised machine learning methods to detect and decipher human disease heterogeneity.


Decoding "Dirty" Data

We decode pediatric phenotypic and genomic datasets using computational and bioinformatics tools to understand their role in human diseases.


Translational Medicine

We leverage “clinical and genomic big data” and apply machine learning to develop diagnostics and therapies to improve sick kids health.

Our Research Philosophy

CiDrep SickKids Research Lab focus on artificial intelligence (AI) and translational research (TR), funded by grants that support discoveries in fundamental science to leverage heterogeneity to accelerate translational medicine to decipher human disease. Our research is an in-house data-driven laboratory that's applying machine learning to develop diagnostics and therapies to improve sick kids health. In 2018, we begun collecting and storing available data that emanate from pediatric phenotypic and research studies. We now have terabytes of data points in our cloud repository and data vault, and continuing to develop machine learning methods and tools to embrace heterogeneity in data that can accelerate translational medicine for diagnostics and therapies to improve health.

Our Funding

We are actively applying for grant funding and other endowment positions to help our research team build and expand our research methods, tools and collaborate with other leading scientists and clinicians to ensure that our work is relevant to sick kids care. We encourage donations, endowments and all funding to support our research. Here's how you can help us. 

Our Team

We are building a diverse lab with researchers, computer scientists, computational biologists, bioinformaticians, data engineers, statisticians and AI scientists, with different areas of expertise to work closely together to better understand human immune system and study human disease heterogeneity.