Ben‐Haim Eran

Technion – Israel Institute of Technology

Papers

Total Citations

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About

Eran Ben-Haim is a pioneering researcher at the intersection of artificial intelligence, soft robotics, and physical computing. His work centers on developing physical neural networks (PNNs)—mechanical systems that emulate brain-like computation—and creating innovative control strategies for soft robotic actuators. In his highly cited 2025 paper "Multistable Physical Neural Networks," Ben-Haim explores how mechanical structures can implement artificial neural networks, offering a tangible alternative to traditional digital AI that leverages the inherent properties of physical materials. This work has already garnered 3 citations, signaling its growing influence in the field. His equally notable contribution, "Dynamic Single‐Input Control of Multistate Multitransition Soft Robotic Actuator," addresses a critical bottleneck in soft robotics: the complexity of multiple control inputs. By demonstrating how a single dynamic input can achieve multiple states and transitions, Ben-Haim simplifies actuation systems, making them more practical for real-world applications. His research bridges fundamental physics and applied engineering, offering elegant solutions that reduce system complexity while expanding functional capabilities. Ben-Haim’s work is essential reading for anyone interested in the future of embodied intelligence, where computation and physical action converge.