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Anton Bernatskiy is a researcher in evolutionary robotics whose work explores the intersection of robot morphology, neural control, and evolvability. His key research areas include soft and rigid-body robot simulation, modular neural network controllers, and the evolution of embodied agents. Bernatskiy’s major contributions demonstrate how robot body plans (morphologies) can fundamentally shape the evolution of intelligent behavior. In his most cited work, “Simulating the evolution of soft and rigid-body robots” (15 citations), he addresses the critical challenge of making robot simulation accessible to new programmers. His influential 2015 paper “Evolving Robot Morphology Facilitates the Evolution of Neural Modularity and Evolvability” (13 citations) shows that modular body plans can bootstrap modular neural controllers, enhancing a robot population’s ability to adapt. Further work reveals that morphological modularity enables robot behavior to scale linearly with environmental complexity (6 citations), and that sparsity in neural networks can drive the emergence of modularity (4 citations). Notably, Bernatskiy also identifies pitfalls where certain robot morphologies can prohibit modular control and disrupt evolution entirely (2 citations). His research provides foundational insights for designing robots that can evolve more complex, scalable, and robust behaviors.