Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore a 54-minute conference talk on AI applications in scientific research, focusing on scientist-in-the-loop frameworks that bridge machine learning and real-world use cases. Discover how these models accommodate varying data, analysis tasks, and existing domain knowledge while optimizing expert effort in scientific workflows. Learn about methods for discovering semantically meaningful structure from data and integrating domain knowledge with learning. Gain insights into the speaker's collaborative approach with scientists to accelerate scientific progress through efficient AI-driven techniques.