52 citations · 54 across the 6 of their papers we have counts for
8 papers
Learning to Harvest Without Collapse in a Regenerative Commons: A Lagrangian Framework
Jose Tupayachi, Xueping Li, Soham Das
The tragedy of the commons poses a multi-agent safety problem: reward-seeking agents can deplete a shared resource, and cooperation among its users does not itself specify how much…
Data-Driven Stress Testing of Intermodal Freight Networks Using GAN-Generated Disruption Scenarios
Xudong Wang, Mustafa Can Camur, Sabarna Choudhuri +1
Intermodal freight networks are increasingly exposed to correlated, multi-mode disruptions, yet resilience assessments often rely on historical or uncorrelated scenarios that under…
Simulating Cognitive Smart Freight Corridors with Agent-Based Models and Reinforcement Learning
Madelaine Martinez-Ferguson, Chun Wang, Mustafa Can Camur +1
Smart freight corridors offer a practical pathway for connected and automated vehicle (CAV) deployment in freight transportation, but physical experimentation is expensive and exis…
Per-Shipment Multi-Agent Reinforcement Learning for Intermodal Freight Routing Under Hurricane Disruption
Aliza Sharmin, Xudong Wang, Mustafa Can Camur +1
Intermodal freight networks face growing disruption risk from climate extremes that degrade multiple corridors simultaneously. To address this, we formulate freight routing as a De…
Spatio-Temporal Graph Convolutional Networks for EV Charging Demand Forecasting Using Real-World Multi-Modal Data Integration
Jose Tupayachi, Mustafa C. Camur, Kevin Heaslip +1
Transportation remains a major contributor to greenhouse gas emissions, highlighting the urgency of transitioning toward sustainable alternatives such as electric vehicles (EVs). Y…
Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol
Haowen Xu, Yulin Sun, Jose Tupayachi +3
Optimizing urban freight logistics is critical for developing sustainable, low-carbon cities. Traditional methods often rely on manual coordination of simulation tools, optimizatio…
Empowering Cognitive Digital Twins with Generative Foundation Models: Developing a Low-Carbon Integrated Freight Transportation System
Xueping Li, Haowen Xu, Jose Tupayachi +2
Effective monitoring of freight transportation is essential for advancing sustainable, low-carbon economies. Traditional methods relying on single-modal data and discrete simulatio…
Towards Next-Generation Urban Decision Support Systems through AI-Powered Construction of Scientific Ontology using Large Language Models -- A Case in Optimizing Intermodal Freight Transportation
Jose Tupayachi, Haowen Xu, Olufemi A. Omitaomu +3
The incorporation of Artificial Intelligence (AI) models into various optimization systems is on the rise. Yet, addressing complex urban and environmental management problems norma…