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About

Jarmo T. Alander is a pioneering researcher in the application of genetic algorithms (GAs) to robotics and industrial automation. His work has fundamentally advanced how evolutionary computation can solve complex control and navigation problems. In his highly cited 2002 paper, "On finding the optimal genetic algorithms for robot control problems," Alander introduced a C++ package that uses a genetic algorithm to optimize the parameters of other genetic algorithms—a meta-optimization approach that has garnered 14 citations. He further demonstrated the power of GAs for autonomous movement in his 1993 work on robot navigation. Beyond robotics, Alander has made significant contributions to manufacturing, including a 2018 survey on telerobotic surface finishing that examines how visuo-haptic feedback can improve remote grinding processes. He has also innovatively applied GAs to materials science, using them to search for strain field parameters in tensile test images (2007). His vision for modular automation is evident in his design of a multiarm assembly cell with object-oriented control (2002). With a career spanning decades, Alander’s research continues to influence the intersection of evolutionary computation, robotics, and industrial engineering.