THANKS FOR A SUCCESSFUL CONFERENCEAbout the Conference
The Commonwealth’s first international gathering of logistics professionals heard from industry leaders about trends and advances in the field. Brought to Virginia by CCALS and Old Dominion University in partnership with CILTNA, the inaugural conference was hosted on the ODU campus in Norfolk, VA, home to one of the world’s safest and most advanced ports and a gateway to multimodal transportation through the US and beyond. The conference brought together leaders from industry, government, and academia to explore how artificial intelligence, digital twins, robotics, and advanced analytics are reshaping freight movement, multimodal logistics, and supply chain resilience.
From AI-powered rail scheduling to smart ports, from ethical AI governance to workforce transformation, attendees explored the latest innovations and practical applications that are transforming logistics networks across rail, maritime, road, and intermodal systems.
Questions
If you have any questions about the Conference, please email conference@ccals.com.
TRACKS
AI in Freight Planning & Optimization
- AI-Powered Freight Matching:Real-Time Mode and Route Allocation
- Intelligent Load Planning:Container, Pallet, and Multi-Modal Optimization
- Last-Mile AI:Route Optimization in Urban and Port-Adjacent Zones
- Predictive Logistics:AI Models for Anticipating Delays Across Modes
- Dynamic Pricing & Demand Forecasting:Machine Learning in Freight Networks
- AI for Cross-Border Logistics:Document Automation, Duty Optimization, and Risk Assessment
- Control Tower 2.0:AI-Driven Orchestration of Global Supply Networks
- Autonomous Logistics Planning:AI Decision-Making for Fleet Routing and Warehousing
- Carbon-Optimized Routing:AI for Low-Emission Freight Planning
- AI in Reverse Logistics:Enabling Circular Logistics Network
Visibility, Risk, and Compliance
- AI-Driven End-to-End Visibility: Real-Time Tracking Across Sea, Rail, and Road
- Proactive Risk Management: AI for Multi-Modal Disruption Prediction
- Trade Compliance Automation: Leveraging AI for Sanctions and Customs Monitoring
- Anomaly Detection in Logistics Flows: AI + IoT Sensor Integration
- AI for ESG Compliance: Automating Sustainability and Emission Reporting
- Supply Chain Stress Testing with AI: Simulating Black Swan Disruptions
AI + Robotics in Logistics Operations
- AI-Augmented Yard Management: Real-Time Asset and Vehicle Coordination
- Human–AI Collaboration in Control Rooms: Enhancing Operational Decision-Making
- Drones & AGVs in Logistics: AI-Enabled Terminal and Warehouse Operations
- Slot Booking Optimization: AI for Dock Door and Appointment Scheduling
AI for Rail Freight Innovation
- Rail Network Optimization: AI to Reduce Dwell Times and Boost Throughput
- Predictive Maintenance in Rail Yards: AI for Asset Health and Reliability
- AI-Driven Train Scheduling: Capacity Planning Across Multi-State Corridors
- Digital Twin Rail Infrastructure: Real-Time Condition Monitoring & Forecasting
- Intermodal Efficiency: AI for Rail–Truck Yard Handoffs
- Computer Vision for Railcar Inspection: Automating Safety and Compliance
- AI-Enhanced ETA Predictions: Going Beyond Traditional Rail Timetables
- Integrating AI with PTC Systems: Advancing Rail Safety
AI for Maritime Logistics Innovation
- Vessel Routing & Fuel Optimization: AI for Sustainable Shipping
- Port Congestion Prediction: Machine Learning with Satellite & AIS Data
- AI in Maritime Risk Management: Storm Avoidance & Cargo Damage Prevention
- Smart Ports of the Future: AI for Berth Allocation & Crane Scheduling
- Container Tracking & Security: Preventing Theft with AI & IoT
- Trade Documentation Automation: NLP for Bills of Lading & Customs Forms
- AI for Maritime Decarbonization: Forecasting & Mitigating Emission Hotspots
- Customs Clearance Prediction: AI Models for Faster Port-of-Entry Processing
Cross-Domain AI for Intermodal Resilience
- Building Integrated Visibility Platforms: Connecting Sea, Rail, and Road with AI
- Federated Learning in Logistics: Privacy-Preserving AI Across Transport Nodes
- Resilient Routing with AI: Lessons from Port & Rail Disruptions
- ESG Monitoring Across Fleets: Unified Emission Analytics for Maritime & Rail
- Autonomous Freight Hubs: Converging AI in Ports, Yards, and Terminals
- Digital Twin-Enabled Emergency Response: Protecting Critical Freight Corridors
Data Infrastructure, Cybersecurity & AI Ethics in Logistics
- Data Foundations for AI: Building Interoperable, Real-Time Data Ecosystems
- Cybersecurity for AI-Enabled Freight Networks: Protecting Ports, Rail, and Intermodal Hubs
- Ethical AI in Logistics: Avoiding Bias, Ensuring Transparency, and Meeting Regulatory Standards
- AI Model Governance: From Development to Deployment in Critical Supply Chains
- Data Sharing in Public–Private Partnerships: Balancing Security and Innovation
Workforce, Skills, and Change Management for AI in Logistics
- AI Adoption Playbooks: Lessons Learned from Global Freight Operators
- Reskilling the Logistics Workforce for the AI Era
- Human–AI Collaboration: Designing Roles for the Augmented Workforce
- Managing Organizational Change in AI-Driven Operations
- Cross-Sector Collaboration Models: Academia–Industry–Government Workforce Pipelines
