Miaomiao Li

National University of Defense Technology

Papers

Total Citations

H-Index

About

Miaomiao Li is a researcher whose work bridges machine learning and financial technology, with a particular focus on extreme learning machines and their applications in automated advisory systems. Her most-cited paper, "Incremental multiple kernel extreme learning machine and its application in Robo-advisors" (2018, 22 citations), introduces a novel approach to enhancing the efficiency and adaptability of learning algorithms for real-time financial decision-making. By developing an incremental multiple kernel framework, Li addresses the challenge of dynamic data streams in robo-advisory platforms, enabling more responsive and accurate portfolio recommendations. This contribution is pivotal for the growing field of AI-driven financial services, where rapid adaptation to market changes is critical. Li’s work demonstrates a clear impact on both theoretical machine learning and practical fintech applications, earning her recognition among researchers exploring the intersection of computational intelligence and finance. Her research not only advances algorithmic design but also provides tangible solutions for modern financial technologies, making her a notable figure in applied machine learning.