We are situated at the intersection of artificial intelligence and healthcare, operating within the Children's Hospital of Eastern Ontario Research Institute (CHEO-RI) and BORN Ontario. Our lab combines expertise in machine learning, health informatics, and bioinformatics to advance early life health outcomes.
Our research is driven by core values of inclusivity, transparency, and collaboration. We create safe(r) spaces for diverse researchers while embracing open science principles. Through curiosity-driven research and innovative approaches, we develop generalized frameworks and solutions that address complex healthcare challenges.
Our research focuses on developing novel artificial intelligence (AI) and machine learning (ML) methodologies. We specialize primarily in creating robust, interpretable AI (e.g., XAI) solutions that address complex challenges in early life health outcomes. Our work spans from theoretical frameworks to practical implementations, leveraging high-performance computing (HPC) infrastructure for large-scale health data analysis.
Our research leverages population-wide maternal-newborn datasets to develop and validate AI-based screening methods that improve healthcare outcomes. Embedded at BORN Ontario, we analyze comprehensive registry data to uncover outcome patterns, identify risk factors, and reveal opportunities for enhanced care delivery. As a prescribed registry, BORN Ontario has the distinct capability to translate research findings into direct clinical impact.
Our work spans from pregnancy through early childhood, addressing critical challenges in maternal-newborn health surveillance, risk assessment, and outcome prediction.
We are committed to developing equitable AI solutions that serve diverse populations and communities. Through careful consideration of bias, fairness, and accessibility, we ensure our innovations benefit all families while maintaining the highest standards of privacy and ethical data use.
If you are interested in joining our lab as a graduate student supervised by Dr. Kevin Dick, he welcomes discussions with prospective students seeking supervision or co-supervision in Computer Science, Health Informatics, or related fields. We particularly encourage applications from diverse and/or marginalized researchers who share our passion for AI in healthcare.
When contacting the lab, please include: - Your research interests and how they align with our lab's focus - Your CV - A brief statement about why you think our lab would be a good fit
We also welcome inquiries from potential postdoctoral fellows, research assistants, and undergraduate summer students interested in AI, machine learning, and healthcare applications. Funding opportunities are available through various channels including NSERC, CIHR, and institutional programs.
