Max Robotics — Global Service Robot Directory + US Certification

About

Michele Braccini’s research lies at the intersection of robotics, complex systems, and synthetic biology, where he investigates how biological principles—such as criticality, phenotypic plasticity, and genetic regulatory networks (GRNs)—can inspire more adaptive and resilient artificial systems. His most-cited work (2022, 16 citations) demonstrates that Boolean network robots poised at a dynamical critical regime—balanced between order and disorder—can exhibit both robustness and a rich repertoire of responses, a property he has exploited for network classifiers. In a 2018 paper (6 citations), Braccini built a bridge between robotics and synthetic biology by using GRN attractor landscapes to model complex behaviors and cell differentiation, offering a framework for designing adaptive robot controllers. More recently, he has pioneered online adaptation mechanisms that provide phenotypic plasticity in artificial systems (2022, 6 citations) and has explored the use of nanowire networks for robot control (2023, 4 citations each), showing how these unconventional substrates can enable real-time behavioral adjustment. With a growing citation record and a focus on foundational principles, Braccini is shaping a new generation of robots that learn and adapt like living organisms.