Editorial Structure

Binbin Cui, Ph.D., C.P.A.
Royal Canadian Mint, Ottawa, ON, Canada
Dr. Binbin Cui is a seasoned finance and AI professional with over 20 years of experience in digital transformation, ERP systems, and data-driven innovation. Holding a PhD in Finance and CPA designation, Dr. Cui currently leads AI-powered financial planning and forecasting initiatives at the Royal Canadian Mint, integrating tools like Microsoft Dynamics 365. An editorial board member for several journals—including Journal of Artificial Intelligence General Science—Dr. Cui reviews manuscripts on algorithmic trading, fraud detection, and behavioral finance. His research explores AI applications in finance, supply chain management, and education, aiming to bridge academic theory with real-world digital innovation.

 

 

Y. Zhang, Ph.D.
University of Pittsburgh, United States
Dr. Y. Zhang is a prominent researcher at the University of Pittsburgh, specializing in artificial intelligence, machine learning, and intelligent systems. With a verified academic profile and over a dozen influential publications in 2024–2025, Dr. Zhang's work spans credit card fraud detection, robotic manipulation, gastrointestinal imaging, and AI-generated text authentication. Notable contributions include applications of transformer models, ensemble learning (LightGBM, XGBoost), and deep reinforcement learning. Dr. Zhang has presented at major IEEE conferences and authored high-impact studies addressing real-world challenges in credit risk prediction, robotics, and content moderation. Their interdisciplinary approach continues to advance innovation in computational intelligence and automation.

 

 

 

Rensi Chen
Senior Analyst – Revenue Management, United States

Rensi Chen is a Senior Analyst specializing in Revenue Management, with a strong academic and professional background in business intelligence and big data analytics. A verified scholar affiliated with the University of Rochester, Chen has contributed to interdisciplinary research at the intersection of data mining, AI, and economic forecasting. Notable works include the design of big data-driven analytics systems and the development of multi-modal AI models for macroeconomic prediction. With experience in both academic research and industry applications, Chen brings practical insight into leveraging large-scale data for strategic decision-making, performance optimization, and predictive modeling in complex business environments.