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About

Chun Ouyang is a leading researcher at the intersection of artificial intelligence, process automation, and healthcare informatics. Her work fundamentally addresses how intelligent systems can be made both trustworthy and practically deployable in high-stakes environments. Ouyang’s most impactful contribution is a landmark systematic review on trustworthy and explainable AI in healthcare, which has garnered 666 citations and critically assesses quality, bias risk, and data fusion in clinical AI applications. She is also a pioneer in the study of Robotic Process Automation (RPA), with her 2019 paper on contemporary themes and challenges accumulating 520 citations—a foundational reference for researchers and practitioners seeking to understand automation’s organizational and technical frontiers. More recently, Ouyang has advanced the discourse on risk-free trustworthy AI, articulating the essential requirements for safe algorithmic decision-making across sectors like education, business, and government. Her work bridges rigorous technical analysis with pressing societal needs, making her a vital voice in shaping how AI systems earn and maintain human trust. Ouyang’s research continues to influence both academic theory and real-world deployment of responsible AI.