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 the foundations of data science, decision-making, and organizational intelligence. He served as the inaugural Academic Director of Purdue's BS Business Analytics and Information Management (BS BAIM) program, contributing to its growth from launch to more than 600 enrolled students within three years. He is currently serving as an associate editor on the editorial board of Harvard Data Science Review.
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 by reweighting between technical training and decision design -- shifting the emphasis from mastering specific modeling 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 professional engagement, Dr. Zhu strives to advance a decision-oriented vision of data science, arguing that lasting value comes not simply from developing more analytical methodology, but from designing intelligent and trustworthy decision systems that enable better human decisions in an AI-enabled world.
