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About

George Karakostas is a researcher whose work centers on distributed algorithms, mobile robotics, and combinatorial optimization, with a particular focus on search-and-rescue and evacuation problems in geometric settings. His most recognized contributions involve the theoretical study of "search-and-fetch" and treasure-evacuation problems, where teams of autonomous robots must locate and retrieve objects on a disk under varying communication constraints. This line of research, which Karakostas helped pioneer, addresses how robots operating with wireless versus face-to-face communication models can optimize search strategies — findings with direct implications for real-world drone-based surveillance and disaster response operations. Across multiple influential publications spanning 2016 to 2023, Karakostas has systematically explored both single-robot and multi-robot scenarios, analyzing trade-offs between communication overhead and algorithmic efficiency. His 2017 paper on two-robot search-and-fetch with different communication models is his most cited work, accumulating 15 citations, while his broader body of work in this domain has collectively gathered over 49 citations. Through rigorous algorithmic analysis and competitive ratio frameworks, Karakostas has helped establish foundational benchmarks for robot coordination theory, making his research valuable reading for students working at the intersection of theoretical computer science and autonomous systems.