Meng Qu Wu

Mengqu Wu is an M.Phil. student at the RAND School of Public Policy and an assistant policy researcher at RAND. His work examines the national security implications of emerging technologies and the strategic challenges created by rapid advances in computation, artificial intelligence, and global economic competition. He studies how quantum information science, machine learning, and advanced modeling techniques can support long-term decisionmaking on issues spanning international security, technological rivalry, and systemic risk.

Prior to joining RAND, Wu spent more than a decade in the private sector in roles at the intersection of computation, quantitative finance, and innovation-driven research. As the quantum applications research lead at Turing Q, he developed NISQ-era optimization methods and quantum machine learning models for complex financial and scientific systems. At DeepBlue Technology, he worked as an artificial intelligence researcher, directing predictive medicine and big-data architecture projects integrating genomics, deep learning, and health-security analytics.

Earlier in his career, Wu served as a quantitative researcher at a Shanghai-based hedge fund, where he designed high-frequency and medium-frequency trading strategies across equities and commodities. He has also worked across macroeconomic analysis, fintech product development, and international business development, collaborating with global family offices, financial institutions, and cross-border investment groups.

Wu holds an M.S. in quantum information science from the University of Southern California, an M.S. in finance from Shanghai Jiao Tong University, and a B.A. in economics and psychology from the University of California, Berkeley. He is fluent in English and Chinese.