Zhiwei Zhu, Ph.D. is a scholar, educator, and former senior executive whose work lies at the intersection of artificial intelligence, data science, and decision governance. He is a Clinical Associate Professor at Purdue University's Daniels School of Business, where he teaches business analytics and investigates how AI is reshaping organizational intelligence, decision-making, and the foundations of data science. He also served as the inaugural Academic Director of Purdue's BS Business Analytics and Information Management (BS BAIM) program, overseeing its growth from launch to more than 600 enrolled students within three years.
Before returning to academia, Dr. Zhu held executive leadership positions at leading global (re)insurance companies, including Swiss Re, SCOR Group, and Assurant Health, where he built and led enterprise analytics operations supporting strategic decision-making, risk management, and business operations through advanced analytics. This experience shaped his central thesis: in the age of AI, the defining challenge — and the ultimate source of competitive advantage — is no longer isolated technical capability, but the design of decision systems that responsibly integrate human judgment with machine intelligence for both professionals and organizations.
A Fulbright U.S. Scholar, Poets & Quants Best Undergraduate Professor, and former industry executive, Dr. Zhu has delivered invited seminars at business schools across Europe and addresses academic and industry audiences on the future of analytics, AI, business, and education.
His recent scholarship—including Data Science at a Fork in the Age of AI: Recognizing Divergent Missions in Research and Education · Harvard Data Science Review—argues that AI represents not merely a technological advance, but a fundamental shift in how data, analytics, and inference are defined and understood. Building on these ideas, he authored the textbook Forecast by Design: Decision-Oriented Time Series Analytics in the Age of AI, which illustrates how AI should transform analytics education in two fundamental ways. First, it reframes forecasting—and, more broadly, data analytics—not as an isolated modeling exercise, but as a decision design process guided by purpose-driven evolution, implementation, and continuous validation. Second, it shifts the emphasis from mastering specific models or coding techniques to learning how to work effectively with AI as both a learning partner and a thinking partner.
through his research, teaching, and industry engagement, Dr. Zhu advances a decision-oriented vision of data science, arguing that lasting value comes not simply from performing more accurate analyses, but from designing intelligent, trustworthy decision systems that enable better human decisions in an AI-enabled world.
