Prof. Matia Yoav

Emergent Structural Autonomy, Soft Robotics, Fluid-Structure Interactions

     I research to challenge the way we perceive matter and the role it has in our future machines. In conventional wisdom, "smart" require external control infrastructure – sensors, processors, power, wiring – creating fundamental constraints on scale, adaptability, and environmental integration. I challenge this paradigm. Electronics and software are not the only path to making things "smart". I vision matter itself – not as passive substrate, but as active participant in logical processes. In my work, material architecture performs roles traditionally assigned to control systems: sensing environmental stimuli, processing information through its physical constitution, and generate response. The material works on behalf of the system function, without external drivers.

     I implement computation through multiscale material topology rather than electronic circuitry or software code. Where conventional approaches translate physical stimuli into electrical signals for processing, I design parametric frameworks that relate mesoscale topology to target logical and mathematical operators. Through this designed architecture and multiphase materials, I demonstrate the direct processing of information in the mechanical domain—routing and modulating organic physical phenomena within the structure: stress fields, thermal gradients, vibrational modes, and wave propagation now form a physical sense-assess-respond cycle through structural geometry and multi-physics coupling while preserving the original structural functionality.

     Through this neuromorphic architecture, the material routes the organic physical phenomena it experiences and modulates them similarly to how an electric signal is processed in artificial neural networks (ANN). This processing is analogous to a sense-assess-response cycle of controllers, only built into the material without wiring, sensors, power sources, processors (CPU), and more.