I am a Data Science Program Manager with a B.Sc. in Biotechnology and a Ph.D. in Biomedical Engineering from the University of Toronto. My career has been shaped by a deep curiosity for solving complex healthcare challenges through data science, artificial intelligence, and multidisciplinary collaboration.Over the past decade, I’ve had the privilege of working on diverse projects across healthcare, pharma, and life sciences, combining advanced computational techniques with biomedical research. During my Ph.D. at SickKids, I developed computational models of brain networks, using approaches like deep neural networks for neurological disease modeling, ensemble machine learning for predictive diagnostics, and Bayesian modeling for treatment outcome prediction. My work also explored unsupervised learning for phenotype clustering and reinforcement learning for personalized healthcare, contributing to innovative solutions for diagnosis and treatment.Beyond my academic research, I’ve published over 20 peer-reviewed articles, secured more than $1.5 million in research funding, and taught university-level courses on data science and biomedical engineering. I’ve also applied my expertise in natural language processing (NLP) and causal inference to improve clinical workflows and healthcare interventions.In addition to my academic journey, I’ve gained over five years of experience as a Management Consultant in AI and Data. Working with life sciences and technology clients across 12 countries, I’ve helped organizations navigate digital transformation, AI enablement, and data-driven strategy development. My goal has always been to align technical insights with strategic objectives to drive meaningful impact.I’m passionate about advancing healthcare through innovative applications of AI, machine learning, and computational modeling. I believe in leveraging technology and collaboration to improve health outcomes and create a better future for all.