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Navigating Network Science and Machine Learning
This chapter features the speaker's educational background and the evolution of their work in computer science, particularly in network science following 9/11. It emphasizes the complexities and limitations of graph representations in machine learning, advocating for more nuanced approaches to analyzing complex systems. The discussion encompasses various topics, including challenges in accurately modeling epidemic tracking and the implications of asymmetric information transmission in economic networks.