GeneDx
Matthew Greenberg is a Senior Machine Learning Engineer at GeneDx, focused on diagnosing diseases in infants and newborns through whole genome and exome testing. Responsibilities include improving the genetic report writing process in collaboration with Genetic Counselors, achieving significant reductions in variant review while maintaining high accuracy. Previously, Matthew led a team at Prescient Edge on federated platforms for the Department of Defense and Intelligence Community, and developed a Continuous Learning framework at GumGum for Computer Vision models. Matthew gained foundational experience at IBM, where patented research improved data cleansing and classifier predictions, along with work in silicon photonics. Matthew holds a B.Sc. (Hons.) in Physics from the University of St Andrews.
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GeneDx
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GeneDx is focused on delivering personalized, actionable insights that improve health outcomes. We sit at the intersection of diagnostics and data science, pairing decades of genomic expertise with an unmatched ability to interpret clinical data at scale. Our exome and genome testing is among the best in the industry. We expect that it will be even more advanced in the future with the help of Centrellis®, our innovative health information platform. Powered by millions of medical records, Centrellis® integrates digital tools with artificial intelligence to ingest and synthesize clinical and genomic data. As a result of our robust test menu, including our exome and genome testing, and the comprehensive insights generated by Centrellis®, we are developing a more complete understanding of complex disease than ever before. This translates to faster diagnosis, more effective treatment plans, and enhanced drug discovery. Our offerings help a whole spectrum of healthcare partners -- clinicians, researchers, health systems, pharmaceutical companies, and payors -- improve patient experiences and advance population health.