The Alsentzer Lab is an interdisciplinary research group in the Department of Biomedical Data Science at Stanford University. Our mission is to leverage machine learning (ML) and natural language processing (NLP) to augment clinical decision-making and expand access to high-quality healthcare. Our lab develops new methods to infuse biomedical knowledge into machine learning algorithms and leverages heterogeneous clinical data, such as electronic health records and genomic data, to provide actionable insights to clinicians, researchers, and patients. We operate at the intersection of computer science, informatics, and medicine, designing methods to improve model trustworthiness and leveraging implementation science to integrate our methods into the healthcare system. We are motivated by the question: how can we design trustworthy machine learning methods that excel in settings with limited annotated data and can be deployed safely and effectively into clinical workflows?

We are hiring! We are looking for motivated students and postdocs interested in advancing trustworthy, deployable ML and NLP for healthcare. See here for more details.