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Explore causality from multi-modal data in this keynote presentation delivered at KDD 2025. Learn from Caroline Uhler, a leading researcher at the intersection of machine learning, statistics, and genomics, as she discusses cutting-edge approaches to causal inference using diverse data types. Discover how multi-modal data can enhance understanding of causal relationships and their applications in genomics and beyond. Gain insights into the latest methodologies for extracting causal insights from complex, heterogeneous datasets. Understand the challenges and opportunities presented by integrating different data modalities for causal analysis. Examine real-world applications where multi-modal causal inference drives scientific discovery and practical solutions. This presentation draws from Uhler's extensive expertise in causal inference, representation learning, and gene regulation, offering valuable perspectives for researchers and practitioners working with complex data systems.
