This track focuses on the latest advancements in blockchain technology and its applications within supply chain management. Researchers are invited to present novel solutions that enhance transparency, traceability, and efficiency in logistics.

This session explores various predictive modeling techniques, including supervised and unsupervised learning, to optimize supply chain processes. Contributions should demonstrate how these models can improve decision-making and operational efficiency.

This track highlights the application of deep learning algorithms in logistics and inventory management. Papers should discuss innovative approaches to enhance demand forecasting, stock optimization, and resource allocation.

This session addresses the critical issue of anomaly detection within supply chain systems using advanced analytical techniques. Researchers are encouraged to present methodologies that identify irregularities and enhance system reliability.

This track focuses on the importance of feature extraction in improving supply chain analytics. Contributions should explore techniques that enhance data interpretation and facilitate better decision-making.

This session examines the role of workflow automation in streamlining supply chain operations. Papers should present case studies or frameworks that demonstrate the impact of automation on efficiency and productivity.