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Explore cutting-edge developments in biomedical AI agents through this comprehensive seminar featuring two expert presentations from Stanford researchers. Learn about Biomni, a revolutionary general-purpose biomedical AI agent developed by Kexin Huang that autonomously executes diverse research tasks by employing action discovery to map biomedical action spaces across 25 domains, integrating LLM reasoning with retrieval-augmented planning and code execution to enable dynamic workflow composition without predefined templates. Discover how this system demonstrates strong generalization across gene prioritization, drug repurposing, rare disease diagnosis, microbiome analysis, and molecular cloning tasks, while generating experimentally testable protocols from multi-modal data analysis. Gain insights from Hanchen Wang's primer on specialized AI agent builds and general methods for biomedical discovery, covering perturbation design, spatial transcriptomics, and cell imaging applications, along with technical implementations including tool-use agents, context engineering, computer use, calibration guarantees, and reinforcement learning approaches. Understand how these AI systems envision collaborative partnerships between artificial intelligence and human researchers to accelerate biomedical discovery, clinical insights, and healthcare advancement across fragmented research workflows and complex experimental datasets.
