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About

Greg Aloupis is a computational geometer and theoretical computer scientist whose research sits at the compelling intersection of algorithms, robotics, and combinatorics. He is best known for his foundational contributions to the theory of **modular self-reconfigurable robotics**, particularly the algorithmic challenges of transforming one robot configuration into another efficiently and reliably. His most influential work focuses on cube-style and crystalline modular robots — systems composed of unit-cube atoms capable of expanding, contracting, and attaching to neighbors. His 2008 paper on linear reconfiguration has garnered 39 citations, establishing key complexity bounds for how these systems can be reorganized. Alongside collaborators, he developed algorithms achieving reconfiguration in O(log n) parallel moves, a significant theoretical advance demonstrating that large robot ensembles can be transformed with remarkable efficiency. His subsequent work extended these results to more realistic physical constraints, bridging the gap between abstract models and practical robotic systems. Aloupis's research has meaningfully shaped how theoreticians and roboticists think about scalable, collision-free reconfiguration, providing rigorous algorithmic foundations for emerging technologies in programmable matter and swarm robotics. His body of work remains an essential reference for researchers entering these fields.