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intelligent behavior it generates, including perception, motor planning, learning, reasoning, and problem-solving. This ambitious initiative promises to offer unprecedented insights into the brain's algorithms
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communicate by flexibly reasoning about what other agents know and want. Recently, we have been exploring how this framework of inferential social learning can be applied to develop socially intelligent
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. This work involves developing novel techniques, algorithms, and software packages that enable more robust and scalable approaches to cybersecurity using AI-based techniques. In addition to technical
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systems. Includes establishing medical reasoning benchmarks and automated / scalable evaluation methods. Developing recommender algorithms to predict specialty care with large-language model based user
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will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA-seq, spatial transcriptomics and
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. This includes integrating LLMs with structured data sources to develop robust computational phenotyping algorithms and scalable models for real-world evidence generation. The role will involve both method
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Center for Biomedical Informatics Research at Stanford University. This position emphasizes evaluating various cancer screening strategies by developing and applying microsimulation models for decision