Dr. Di Wu is an economist and data scientist who applies econometric modeling, machine learning, and advanced analytics to inform policy, regulatory, and legal decision-making. Dr. Wu's work centers on the statistical analysis and economic modeling of data throughout legal processes. He brings particular expertise to matters involving employment, antitrust, and corporate strategy, applying advanced quantitative techniques to extract insights and support sound decision-making.
Previously, Di served as a Financial Economist at the Public Company Accounting Oversight Board (PCAOB), where he conducted rigorous economic analyses to support inspections. He was also a Principal at Edgeworth Economics and a Consulting Economist at Littler Mendelson, leading high-impact engagements across labor, employment, and antitrust matters. His experience spans all stages of litigation and advisory work—from data consolidation and model development to damage quantification and expert support. He has collaborated with attorneys, data scientists, and executives to deliver clear, actionable insights from complex datasets.
Dr. Wu earned his Ph.D. and M.S. in Applied Economics and Management from Cornell University and holds a B.S. in Applied Economics and Mathematics from Purdue University.
