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About

Clayton B. Jackson is a rising researcher at the intersection of computational neuroscience, soft robotics, and bio-inspired control systems. His primary contributions lie in developing Synthetic Nervous Systems (SNS)—biologically plausible neural networks that enable adaptive, compliant control for robotic platforms. Jackson’s most influential work, “SNS-Toolbox: An Open Source Tool for Designing Synthetic Nervous Systems” (2023, 10 citations), provides a critical open-source framework for integrating dynamic, conductance-based neuron models with cyber–physical systems, making advanced neural control accessible to the broader robotics community. He has also pioneered dynamic simulations for soft-bodied locomotion, including a 3D model of a worm robot performing peristaltic movement (2025) and a compliant worm robot amenable to neural control (2023). His mechanical design of a feline robot for dynamic scaling testing (2024) further demonstrates his versatility in bridging neural control with legged locomotion. Though early in his career, Jackson’s work is already shaping how researchers design and test neurally-controlled, soft robotic systems for traversing complex, confined environments—a critical step toward more adaptive and resilient autonomous machines.