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Arjun Muralidharan is a researcher specializing in communication-aware robotics, autonomous systems, and wireless communications, with a particular focus on the intersection of robot motion planning and real-world communication constraints. His work addresses a fundamental challenge in modern robotics: how unmanned vehicles can intelligently navigate to optimize both mission objectives and communication performance simultaneously. Among his most influential contributions is a comprehensive review of communication-aware robotics (2021, 40 citations), which has become a key reference for researchers seeking to understand how realistic wireless environments shape robotic navigation strategies. His pioneering work on distributed beamforming using mobile robots — spanning multiple papers from 2016 to 2017 — demonstrated how teams of unmanned vehicles can function as virtual antenna arrays, cooperatively transmitting information to remote stations while minimizing energy consumption (26 and 16 citations, respectively). Muralidharan has also made significant theoretical contributions to connectivity-seeking behavior in autonomous systems, mathematically characterizing how far a robot must travel before establishing a reliable communication link. This body of work, accumulating over 118 total citations, provides both theoretical foundations and practical frameworks that are increasingly relevant as autonomous systems are deployed in complex, communication-constrained environments such as disaster response, exploration, and military operations.