Emadodin Jandaghi

University of Rhode Island, The King's College

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About

Emadodin Jandaghi is pushing the boundaries of intelligent robotics at the intersection of soft robotics, multi-agent systems, and fault-tolerant control. His research focuses on two critical challenges: enabling soft continuum robots—like trunk-inspired manipulators—to detect and isolate faults autonomously, and coordinating networks of robotic manipulators that must learn and synchronize despite unknown dynamics. In his highly cited 2023 work on a soft trunk robot, Jandaghi developed an adaptive radial basis function neural network approach for dynamics learning-based fault isolation, demonstrating how data-driven models can diagnose failures in highly deformable systems. That same year, his motion dynamics modeling and fault detection framework for soft trunk robots (16 citations) provided foundational tools for ensuring reliability in these emerging platforms. Most recently, his 2024 paper introduced a novel two-layer distributed adaptive learning control strategy for nonlinear multi-agent systems, enabling heterogeneous robots to synchronize and learn under complete dynamic uncertainty—a significant step toward resilient, decentralized robotic teams. With multiple high-impact publications in rapid succession, Jandaghi is establishing himself as a rising voice in adaptive control and soft robotics, bridging theory and practical deployment.