Dr. Suchi Saria is an Assistant Professor at Johns Hopkins University where she is also the director of the Machine Learning and Healthcare Lab.
My interests span Bayesian and probabilistic modeling approaches for addressing challenges associated with modeling and prediction in complex, real-world temporal systems. My recent work has focused on large scale modeling with Bayesian methods, methods for counterfactual reasoning, Bayesian nonparametrics, and Gaussian Processes. I am also excited about addressing challenges related to the use of data-driven tools for decision-making.
I direct the Machine Learning and Healthcare Lab at Johns Hopkins University. We are interested in enabling new classes of diagnostic and treatment planning tools for healthcare—tools that use statistical machine learning techniques to tease out subtle information from “messy” observational datasets, and provide reliable inferences for individualizing care decisions. In order to accomplish these goals, our lab (1) identifies domains/disease areas where such approaches can make an impact, (2) identifies gaps where current technologies fail, (3) designs new statistical machine learning techniques that solve associated fundamental computational challenges, and (4) develops and deploys solutions to measure impact.
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