Azadeh Gholami

Institute for Advanced Studies in Basic Sciences

Papers

Total Citations

H-Index

About

Azadeh Gholami’s research lies at the intersection of robotics, artificial intelligence, and formal modeling, with a particular focus on behavior learning and task performance analysis in autonomous systems. Her most-cited work, “A learned soccer goalkeeper Petri net model” (2017), introduces an innovative approach to modeling a robot goalkeeper’s decision-making processes using Petri nets. This paper, with 4 citations, demonstrates her ability to combine qualitative and quantitative analysis to enhance robotic behavior in dynamic environments. By applying formal methods to robot learning, Gholami provides a structured framework for understanding and improving task performance across varied scenarios. Her contributions are especially relevant to the field of robotic soccer, where adaptive, real-time decision-making is critical. Though early in her career, Gholami’s work signals a promising trajectory in model-based robotics, offering tools that bridge theoretical modeling and practical application. Her research is valuable for students and researchers interested in how formal models can be leveraged to create more intelligent, responsive autonomous agents.