Research Work
“Feras Naser decided to return to Academia so he can be surrounded by a supportive community, he can pursue his research interests and academic work in an enriching and supportive environment.”
Feras Naser
Research Projects & Interests
Multi Agent Systems and Agentic AI for Rail Infrastructure Managment
Railway systems operations consist of complex, interacting subsystems. Various organizations—such as infrastructure owners and train operating companies—along with key stakeholders like passengers and contractors, hold competing interests and conflicting demands.
Capturing this complexity effectively to optimize for the lowest whole-system life cycle cost requires specialized modeling techniques. Multi-Agent Systems and Agentic AI, combined with mathematical optimization methods, provide a robust framework for modeling these decentralized interactions to achieve optimal whole-system life cycle costs.
That said, this approach inherently relies on modeling operational uncertainty and monetizing non-monetary variables, including safety, risk, and political trust.
Week 1 – Understanding the Scope of this research and the tools that I will be using in this research