Ruimeng Hu

Ruimeng Hu is an Associate Professor at the University of California, Santa Barbara (UCSB), with a joint appointment in the Department of Mathematics and Department of Statistics and Applied Probability. They hold editorial roles at Digital Finance and Mathematical Finance, co-organizing special issues on deep learning and machine learning in finance. Their research focuses on interdisciplinary areas including machine learning, financial mathematics, stochastic control, game theory, and climate modeling.

Education:

• Ph.D. in Statistics and Applied Probability, UCSB (2018)
• M.A. in Mathematical Statistics, UCSB (2014)
• B.S. in Pure and Applied Mathematics, Peking University (2012)

Research Interests:

• Machine learning applications in finance and climate science
• Stochastic control and game theory in multi-agent systems
• Development of physics-informed neural networks
• Analysis of stochastic partial differential equations

Their work bridges theoretical advancements with practical tools for financial risk management and environmental modeling.

Key Contributions:

• Organized international conferences like the 3rd ACM International Conference on AI in Finance (ICAIF-22)
• Founded World Online Seminars on Machine Learning in Finance
• Developed frameworks for adversarial games and pandemic control using game theory and reinforcement learning

Labs & Collaborations:

• Center for Financial Mathematics & Actuarial Research (UCSB)
• Active in interdisciplinary initiatives like the Financial Mathematics Mentoring Initiative