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This talk presents Texera, an open-source cloud-based platform developed at UC Irvine since 2016 that enables collaborative data science, AI, and ML through workflows. Learn how Texera supports users with various technical backgrounds, including those with limited coding skills, domain scientists, and ML experts, to conduct AI-centric data science with Google Docs-like collaboration features. Discover the system's rich capabilities including shared editing and execution, version control, commenting, debugging, multi-language user-defined functions (Python, R, Java), and integration with state-of-the-art AI/ML techniques. Explore how its parallel backend engine enables scalable computation on large datasets using computing clusters, allowing bioinformaticians to elastically request AWS resources for computationally intensive jobs. Professor Chen Li, an IEEE fellow and ACM Distinguished Member from UC Irvine, discusses the research challenges encountered during development, their solutions, and demonstrates use cases in both educational and scientific communities.
