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My recent work deals with learning probabilistic models using expert advice. Specifically, we focus on a class of probabilistic models called cutset networks which allow fast inference. Our algorithm learns concise and accurate cutset networks from data using expert advice in the form of monotonic influence statements. Since cutset networks are interpretable, the learned models can help the expert understand relations between risk factors for medical conditions like Gestation Diabetes.