In the ever-evolving landscape of engineering, the fusion of network science and graph theories has emerged as a dynamic force, revolutionizing the way we represent, design, model, and optimize complex systems. Networks, defined by nodes and edges, are particularly effective for modeling the interactions and interdependencies among individual entities in complex systems. Networks have become the cornerstone for comprehending the intricate relationships underlying a myriad of engineering domains. From transportation networks optimizing urban mobility, power grids ensuring energy efficiency and resilience, and social networks shaping human interactions to biological networks inspiring human-engineered system design, the application of network science and graphs in engineering spans a vast spectrum of disciplines. This JMD-JCISE webinar is dedicated to promoting the dissemination of knowledge on complex networks in engineering systems and design, and to highlighting the latest advances at the intersection of network science, graph theory, AI, and engineering.
Date: April 17, 2026
Time: 10:00 AM (Eastern Time)
Webinar Agenda
• 10:00 – 10:15 AM: Introduction
• 10:15 – 11:05 AM: AE Overview
• 11:05 – 11:25 AM:Invited Talks
• 11:25 – 11:30 AM: Q&A / Discussion
• 11:30 – 11:45 AM: Closing: Optional Networking Session
John Morris
Morris, J., Mocko, G., and Wagner, J. (April 30, 2025). “Unified System Modeling and Simulation via Constraint Hypergraphs.” ASME. J. Comput. Inf. Sci. Eng. June 2025; 25(6): 061005. https://doi.org/10.1115/1.4068375
Giota Paparistodimou
Paparistodimou, G., Knight, P., Robb, M., and Hughes, G. (May 12, 2025). “Dynamic Dual-Layer Network Resilience Assessment as a System Architecting Tool.” ASME. J. Mech. Des. November 2025; 147(11): 111401. https://doi.org/10.1115/1.4068458
Saeid Bayat
Bayat, S., Shahmansouri, N., Peddada, S. R. T., Tessier, A., Butscher, A., and Allison, J. T. (October 29, 2025). “Can Graph Neural Networks Help Identify Promising Thermal Management System Architectures Among Vast Numbers of Possibilities?.” ASME. J. Mech. Des. May 2026; 148(5): 051701. https://doi.org/10.1115/1.4069829
Yuliang Li
Zheng, J., and Li, Y. (October 30, 2025). “An Integrated Task-Parameter Network Framework with Sensitivity Mapping and Path Enumeration for Objective Dependency Analysis in Complex Design Processes.” ASME. J. Mech. Des. May 2026; 148(5): 051401. https://doi.org/10.1115/1.4069895