Qinxu Ding

Qinxu Ding currently serves as a Lecturer in the Finance Programme at the School of Business, Singapore University of Social Sciences (SUSS), where he brings a rich blend of academic expertise and practical experience in FinTech, blockchain, and artificial intelligence. His role involves designing and delivering innovative curriculum modules that integrate advanced machine learning techniques with financial applications, equipping students with cutting-edge skills in explainable AI, recommender systems, and data-driven decision-making. Qinxu’s research interests focus on explainable machine learning, which enhances transparency and interpretability in complex models—an essential aspect in financial technology and blockchain solutions.

In addition to his teaching responsibilities, Qinxu leads key projects that explore the intersection of AI and blockchain technology. His team is actively engaged in developing interoperability blockchain platforms aimed at connecting disparate blockchain networks, fostering collaboration, and unlocking new value propositions for blockchain companies. His expertise in numerical methods, including spline analysis and fractional calculus, supports the development of sophisticated algorithms for financial modeling and risk assessment.

With a solid background in applied and computational mathematics, Qinxu leverages tools such as MATLAB, Python, and LaTeX to implement advanced machine learning models and numerical solutions. His collaborative work with Alibaba teams exemplifies his ability to translate theoretical research into real-world applications, particularly in areas like recommender systems and AI-driven financial analytics. Through his multifaceted role, Qinxu Ding continues to contribute significantly to the evolving landscape of FinTech, blockchain, and AI, fostering innovation and knowledge transfer within the academic and industry communities.