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.

Dr. Chenxiao Xu is an applied mathematician and AI researcher specializing in machine learning, causal discovery, and multivariate time-series analysis. His work integrates deep learning, computational modeling, and large-scale data analytics to solve complex problems in finance, energy systems, and industrial forecasting. He has developed advanced causal graph learning frameworks, interpretable time-series models, and end-to-end AI pipelines for solar irradiance prediction, flight-engine anomaly detection, and household electricity forecasting. Dr. Xu has published extensively in top ACM and IEEE conferences and actively contributes as a reviewer in major AI journals. His research continues to focus on interpretable, fair, and scalable AI systems.

Research area: Machine Learning, Causal Discovery, Time-Series Analysis, Deep Learning, Industrial Forecasting, AI Explainability

Dr. Vishwanadham Mandala is a leading expert in big data, AI, machine learning, and data engineering, with significant contributions to data science and analytics. Currently serving as Enterprise Architect - Data at Cummins, he focuses on AI-driven solutions in automotive safety, manufacturing, and predictive maintenance. Dr. Mandala has authored numerous papers on topics like AI-based recommendation models, predictive failure analytics, and real-time engine failure prediction. His research also explores big data lake houses, data integration, and optimizing supply chains, making him a recognized figure in the field of advanced data analytics and artificial intelligence.