Max Robotics — Global Service Robot Directory + US Certification

About

Pooyan Jamshidi is a researcher whose work sits at the intersection of self-adaptive systems, highly configurable software, and autonomous robotics. His research addresses one of the most pressing challenges in modern software engineering: how complex systems can intelligently adapt to dynamic, uncertain environments without constant human intervention. His most influential contribution, "Transfer Learning for Improving Model Predictions in Highly Configurable Software" (2017, 86 citations), demonstrated how transfer learning techniques can dramatically improve performance modeling across different deployment contexts — a significant breakthrough for systems with vast configuration spaces. Building on this foundation, Jamshidi has made substantial contributions to model-based adaptation for robotics software, developing frameworks that enable autonomous robots to respond effectively when real-world conditions diverge from design-time assumptions. His more recent work on CaRE tackles the notoriously difficult problem of diagnosing root causes of configuration faults in highly configurable robotic systems, offering systematic approaches to a challenge that grows exponentially with system complexity. Collectively, Jamshidi's research empowers engineers to build more resilient, self-managing systems — making him a notable voice in the fields of software engineering, autonomous systems, and machine learning for system optimization.