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Gamal Sallam is a leading researcher in multi-robot systems, with a primary focus on autonomous deployment techniques for critical applications such as search-and-rescue and environmental monitoring. His work addresses the fundamental challenge of coordinating robot teams in GPS-denied or hazardous environments where human intervention is impossible. Sallam’s most influential contribution is the development of the COVER (Cooperative Virtual Force Robot Deployment) technique, which refines traditional virtual force approaches to achieve purposeful, rather than random, robot placement. His 2016 paper, "Multi-Robot Deployment Using a Virtual Force Approach: Challenges and Guidelines," has garnered 11 citations and serves as a key reference in the field. In his 2015 work, he introduced a landmark criticality-based method for GPS-free deployment in rescue operations, earning 8 citations. Sallam’s research is distinguished by its practical validation, including real experimental analyses alongside simulations, as demonstrated in his 2018 study. His two-stage deployment framework (2020) further advances fairness in autonomous robot distribution. With a cumulative impact of over 30 citations, Sallam’s work is essential reading for researchers and students interested in cooperative robotics, autonomous navigation, and disaster-response technology.