Somayeh Sojoudi

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About

Somayeh Sojoudi is a researcher specializing in cloud and fog robotics, human-robot interaction, and networked robotic systems. Her work addresses one of the most pressing challenges in modern robotics: bridging the gap between cloud-based computational power and the real-time demands of dynamic robotic control. Sojoudi's most influential contribution, "A Fog Robotic System for Dynamic Visual Servoing" (2019, 46 citations), introduced innovative fog computing architectures that reduce network latency inherent in cloud-connected robots, enabling more responsive and reliable visual servoing in dynamic environments. This work has become a key reference for researchers tackling latency-sensitive robotic applications. Beyond fog robotics, Sojoudi has made notable strides in human-robot interaction, developing cloud-based frameworks such as the Human Augmented Robotic Intelligence (HARI) system, which enables humanoid robots to automatically mirror human gestures for applications like semaphore communication. Her 2022 work on motion segmentation and synthesis further demonstrates her commitment to making cloud-based teleoperation more practical by intelligently compensating for network delays. Collectively, her research portfolio reflects a consistent focus on making networked robotic systems smarter, more adaptive, and genuinely deployable in real-world human-centered environments.