Zhuo Jin

Professor Zhuo Jin serves as Professor of Actuarial Studies and Research Director in the Department of Actuarial Studies and Business Analytics at Macquarie Business School, Macquarie University. He concurrently holds the position of Co-Director for the Centre for Emerging Risks and maintains affiliations with four university research centers: Data Horizons, Smart Green Cities, Emerging Risks, and Health at Work.

His research program integrates advanced computational techniques with traditional actuarial frameworks, covering stochastic optimal control, mathematical finance, and numerical methods for stochastic systems. Specific expertise includes dividend optimization, reinsurance modeling, systemic risk analysis, and emerging domains like cyber risk, climate risk, and pandemic risk. Recent work increasingly incorporates artificial intelligence methodologies including reinforcement learning and large language models for textual analysis in financial contexts.

Analysis of 2025 publications reveals strong emphasis on hybrid computational approaches solving complex actuarial problems. Key trends include deep learning integration with mean-field games, hidden Markov model applications in portfolio selection, Volterra process modeling for mortality risk, game-theoretic insurance solutions for EV infrastructure, and co-integration analysis for pension fund strategies across interconnected markets.

Research is supported by the Hong Kong Research Grants Council (RGC) and other funding bodies. As Research Director, Jin oversees departmental research strategy while mentoring students. He maintains professional standing as an Associate of the Society of Actuaries (ASA) and serves as Series Editor for World Scientific's Advances in Statistics, Probability, and Actuarial Science book series.

Jin's collaborative work spans multiple risk-focused research centers at Macquarie University, particularly the Centre for Emerging Risks where he develops frameworks addressing cyber, climate, and health-related systemic vulnerabilities through interdisciplinary team structures.