Mikhail Rudoy

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About

Mikhail Rudoy is a theoretical computer scientist whose work lies at the intersection of computational geometry, combinatorial reconfiguration, and algorithmic complexity. His research focuses on understanding the fundamental limits of motion planning and rearrangement problems, often proving that seemingly simple tasks are computationally intractable. Rudoy’s most cited work, “Computational Complexity of Motion Planning of a Robot through Simple Gadgets” (2018, 12 citations), introduces a general theory for analyzing robot motion through stateful gadgets—a framework that unifies many classic puzzles and robotic pathfinding challenges. He further explores the hardness of token swapping on trees (2021, 4 citations), demonstrating that even on restricted graph structures, optimal rearrangement remains NP-hard. These contributions provide essential tools for classifying the complexity of problems in robotics, puzzle design, and combinatorial optimization. Rudoy’s work is notable for its clarity and elegance, offering deep insights into why certain problems resist efficient solutions. His research continues to influence both theoretical computer science and practical algorithm design, making him a valuable voice for students interested in the boundaries of computational tractability.