Data Science & Intelligent Decision-Making: Technological Innovation and Practical Applications

Data science and intelligent decision-making have emerged as core drivers of transformation across public governance, business operations, and educational systems. This session focuses on technological breakthroughs and actionable practices in the field, exploring how advanced data analytics, machine learning, and decision support systems can solve complex real-world problems—from optimizing organizational operations and risk management to enhancing resource allocation and policy-making efficiency. We invite submissions that present theoretical innovations, empirical research, or case studies, with an emphasis on validated methodologies, scalable solutions, and cross-disciplinary applications.

In line with the symposium’s theme of "Education Transformation", this session further explores how data science and intelligent decision-making can be integrated into higher education curricula (e.g., business administration, data science, public management, STEM programs). We welcome research on interdisciplinary teaching models, hands-on training frameworks, industry-academia collaboration mechanisms, and competency-based talent cultivation—aiming to equip students and professionals with the analytical skills, systems thinking, and decision-making capabilities needed to thrive in a data-driven era.

We invite contributions on Advanced data analytics for intelligent decision support, Machine learning and AI-driven decision optimization, Data-driven risk management and policy-making, Intelligent decision systems in business, governance, and education, Interdisciplinary curricula design for data science and decision-making skills, and Industry-academia partnerships in fostering decision-making competence.

Session Chairs

Prof. Luis Martinez Lopez, University of Jaén, Spain

Prof. Mohammed Aquil Mirza, The Hong Kong Polytechnic University, Hong Kong

Dr. Jian Min, Wuhan University of Technology, Wuhan