Michael Beigl

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About

Michael Beigl is a pioneering researcher at the intersection of printed electronics and neuromorphic computing, with a focus on enabling intelligent, flexible systems for soft robotics, wearables, and IoT devices. His major contributions include the realization and training of the first inverter-based printed neuromorphic computing system (2021, 18 citations), a breakthrough that demonstrates how low-cost, flexible substrates can support biologically-inspired spiking neural networks. Beigl’s work addresses the critical challenge of integrating electronic functionality into soft materials, circumventing the limitations of rigid silicon technologies. He has also advanced the practical fabrication of printed circuits through crossover-aware placement and routing techniques for inkjet-printed electrolyte-gated field-effect transistors (EGFETs), enabling low-power, high-mobility devices. More recently, his analog printed spiking neuromorphic circuit (2024) pushes the frontier of energy-efficient, customizable computing for emerging domains. Beyond hardware, Beigl explores novel human-computer interaction with projects like “Things that hover” (2011) and personalized health monitoring via “Fit2Ear” (2024). With a growing citation impact and a portfolio spanning from fundamental device physics to applied wearable systems, Beigl is a leading voice in making intelligence truly ubiquitous and conformable.