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Lydia Kavraki made her first move between worlds when she left Greece to do a PhD in computer science at Stanford University. Drawn to the human potential of robotics, Kavraki studied how robots—from assembly line “arms” to autonomous machines—assess the obstacle-laden world and move around in it. She then created an algorithm that rapidly generates a path for a robot to follow through a given environment, using descriptions of how the robot moves, the space it’s in, obstacles it must navigate and its beginning and end points. Today, most papers on robot-path planning cite her algorithm, and engineers in the automotive industry are using variations of it to build better robotic assembly lines. Kavraki, meanwhile, has moved to a new research world, applying the rules of her algorithm to predict how two molecules will move through space and interact with each other—crucial to designing drugs. Intense and determined, Kavraki finds the two problems closely linked: “There is a potential here for solving problems that could affect our lives, whether it’s a robot that helps disabled people get out of bed or a tool that helps find a compound to treat disease.”