Kean Researcher Uses AI to Improve Port-Area Freight Efficiency Across New Jersey

Kean University Assistant Professor Dan Liu, Ph.D., is leading innovative research with the New Jersey Department of Transportation (NJDOT) to enhance port-area freight efficiency through artificial intelligence (AI).

The project advances Kean’s growing leadership in AI and data-driven research, including the launch of New Jersey’s first bachelor’s degree in AI. Liu’s team is developing AI tools that analyze real-time freight activity, infrastructure usage and traffic patterns to optimize logistics operations and support smarter infrastructure investment across New Jersey’s most critical freight corridors.

“Our students use AI models and freight data to structure information and make more accurate predictions,” said Dan Liu, who is part of Kean’s College of Business and Public Management. “Once validated, these tools can guide NJDOT in making informed investments and in accessing policy impacts on statewide freight performance.”

Kean students play a critical role, working on data processing, model validation, and visualizing traffic patterns. The hands-on experience equips them with skills in machine learning, logistic and sustainable operations.

“Kean’s emphasis on AI and interdisciplinary research has been fundamental,” said Haoxiang Liu, a senior finance major. “We’re gaining exposure to technologies that connect management, data science and engineering, preparing us for careers that shape modern supply chain systems.”

Jin Wang, Ph.D., dean of Kean’s College of Business and Public Management, said the project reflects Kean University’s expanding role as a hub for applied research that connects students directly to statewide innovation.

“Our programs emphasize real-world learning that drives public impact,” Wang said. “This collaboration with NJDOT showcases how our faculty and students work together to solve complex challenges, use emerging technologies responsibly, and contribute to a more efficient and sustainable New Jersey economy.”

The research focuses on New Jersey’s busiest freight corridors, including Jersey City and Newark, where limited parking space and dense transportation networks pose unique challenges.

“Traditional models no longer capture the fast-changing dynamics of urban freight,” Dan Liu said. “My goal is to bridge that gap by combining advanced AI modeling with practical policy applications.”

The team is integrating real-time freight data movement and AI-driven route optimization to improve delivery reliability and reduce congestion. Early results show that incorporating dynamic freight trip data strengthens the flexibility and accuracy of freight distribution models.

Kean students are also using a range of technical and analytical skills, from data engineering to machine learning, to apply AI in ways that make freight and logistics operations more sustainable.

“There are urgent planning and operational questions in freight shipping and urban delivery,” Dan Liu said. “Our work is helping to anticipate and respond to those needs.”