Zhiwei Zhu, Ph.D., is a scholar, educator, and former senior executive whose work sits at the intersection of artificial intelligence, data science, and decision governance. He serves as a Clinical Associate Professor at Purdue University’s Daniels School of Business, where he teaches business analytics and explores how generative AI is transforming both organizational intelligence and the foundations of data science.
Before returning to academia, Zhu held executive leadership roles at Swiss Re, SCOR, and Assurant Health, where he built and led enterprise analytics units responsible for risk modeling, portfolio optimization, and strategic decision support. His industry experience informs his central thesis: the real challenge of AI is not computational capability, but how organizations design decision systems that responsibly integrate machine-generated insights.
His recent scholarship—including contributions to Harvard Data Science Review and INFORMS publications—argues that generative AI represents not merely a technical milestone but a conceptual shift in how data, models, and inference are understood. He writes and speaks widely on the transition from structured analytics to AI-enabled reasoning, and on the need for governance frameworks that align technological power with human judgment.
A Fulbright U.S. Scholar, Zhu has delivered invited seminars at business schools across Europe and regularly addresses academic and executive audiences on the future of analytics education. His work advances a decision-oriented approach to forecasting and data science, emphasizing that precision alone does not create value—designing intelligent, accountable decision systems does.
