Interested in CR2C2 activities and engagement opportunities?
11:30 AM - 1:00 PM
Retail supply chains operate at extreme national scale — thousands of suppliers, hundreds of distribution centers, millions of SKUs, and billions of yearly transactions — all driven by highly dynamic demand patterns. This talk presents how AI, machine learning and OR are transforming retail logistics from reactive operations into intelligent, predictive systems.
We explore a portfolio of AI solutions deployed across the supply chain: connected planning with unified demand-supply-finance signal ingestion; ETA predictability achieving high accuracy gains through multi-modal ML models; agentic AI-driven supplier performance tracking; and a real-time inventory signal into a command center delivering automated root cause analysis across several hundred stores and several thousand items.
Beyond current deployments, we present a vision for autonomous supply chains built on four pillars — visibility, prediction, simulation, and adaptive response — enabled by digital twin architectures, scenario simulation engines, and AI agents that coordinate decisions across systems rather than silos. We conclude with key takeaways on data integration as the foundation of logistics intelligence, the imperative of designing resilience into supply networks, and how collaboration between academia and industry accelerates the path from research to deployment at scale.
Abdullah Al Khaled, PhD is a Senior Manager II of Data Science at Walmart Global Tech, where he leads a high-performing team of data scientists and engineers driving AI, machine learning, and optimization initiatives across retail merchandising, replenishment, and supply chain systems. With over 15 years of experience spanning retail, healthcare, and technology, he specializes in translating advanced analytics—including agentic AI, machine learning, simulation, and mathematical optimization—into large-scale, production-ready solutions.
At Walmart, Abdullah has led the development of enterprise AI platforms and decision systems that power forecasting, inventory and replenishment optimization, logistics, and intelligent automation across global operations; delivering significant cost savings and substantial revenue growth. His work focuses on deploying agentic AI for real-time decision-making and building scalable ML, simulation, and optimization applications that deliver significant operational efficiencies and business impact.
A recognized innovator, Abdullah holds multiple patents in optimization and supply chain technologies and has contributed to research in transportation systems and industrial engineering. He is an active member of professional organizations such as INFORMS and IISE, where he has held leadership roles supporting the advancement of operations research and analytics communities. His work bridges the gap between theoretical rigor and industrial-scale deployment, advancing the role of AI in next-generation mobility and logistics ecosystems.
Dr. Khaled holds a PhD in Industrial and Systems Engineering from Mississippi State University. His research has been published in leading journals including Transportation Research Part B, Applied Soft Computing, International Journal of Production Research, Computers & Industrial Engineering, International Journal of Production Economics, and Neural Computing and Applications, along with contributions to Transportation Research Board and other conference proceedings.