author
Jingwu Tang
Works at the intersection of AI, decision-making, and social impact, studying how algorithms shape real-world choices. His research blends reinforcement learning, game theory, and machine learning with an eye toward practical problems.
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About the author
A researcher in Carnegie Mellon University’s Societal Computing PhD program, he focuses on decision-making, algorithmic game theory, and reinforcement learning. His online profiles and publication listings show work spanning machine learning, auctions, and socially relevant AI systems.
His personal site highlights recent papers at major venues, while academic indexes and author pages connect his work to topics like auction design, multi-objective learning, and broader questions about how intelligent systems make choices. Taken together, they present a scholar interested not just in technical performance, but in how AI can be used thoughtfully in complex settings.