Max Robotics — Global Service Robot Directory + US Certification

About

Murtadha Alsayegh is a leading researcher at the intersection of multi-robot systems, information theory, and privacy-preserving autonomy. His work fundamentally addresses how teams of robots can coordinate effectively under real-world constraints—limited communication bandwidth, unknown environments, and the need to protect sensitive data. His most cited paper (11 citations) introduces a scalable, incremental motion planning algorithm for decentralized robots gathering information from unknown spatial fields, a critical contribution for environmental monitoring and search-and-rescue operations. Alsayegh also pioneered lightweight communication protocols (9 citations) that enable efficient information synchronization when bandwidth is scarce, directly tackling contested or resource-limited scenarios. Notably, his work on privacy-preserving multi-robot task allocation (4 citations) uses secure multi-party computation to allow robots from different organizations to collaborate without revealing proprietary data—a breakthrough for commercial and defense applications. His exploration of oblivious Markov decision processes (2 citations) further extends cooperative planning to settings where parties have partial knowledge. With a growing citation record and a focus on practical, deployable solutions, Alsayegh is shaping the future of trustworthy, efficient multi-robot coordination in the wild.