Evgenya Pergament

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About

Evgenya Pergament is a leading researcher at the intersection of cloud robotics, networked systems, and machine learning. Her work addresses a critical challenge in modern robotics: enabling resource-constrained platforms—such as low-power drones—to run computationally intensive deep neural networks for tasks like perception and object detection. In her highly influential paper, "Network Offloading Policies for Cloud Robotics: A Learning-Based Approach" (2019, 15 citations), Pergament pioneered adaptive offloading strategies that intelligently decide when to process data locally versus in the cloud, balancing latency, bandwidth, and energy constraints. This contribution has become foundational for scalable, real-time robotic systems operating in dynamic environments. Her research not only advances the practical deployment of autonomous robots but also bridges the gap between cloud computing and edge intelligence. With her work cited by peers developing next-generation robotic architectures, Pergament is recognized for shaping how robots leverage distributed computation to overcome hardware limitations. Her achievements underscore a commitment to making sophisticated AI accessible to even the most resource-limited machines, a key enabler for future autonomous systems.