Ryad Benosmanz

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About

Ryad Benosmanz is a pioneering figure in computational neuroscience and neuromorphic engineering, with a focus on bioinspired vision systems and event-driven sensing. His research bridges biology and robotics, particularly through the study of optic flow—the visual motion pattern used by insects like bees and flies to navigate and avoid collisions. Benosmanz’s major contribution lies in developing algorithms that segregate translational and rotational components of optic flow, enabling mobile agents to estimate relative nearness to obstacles in real time. His 2015 paper on a bioinspired event-driven collision avoidance algorithm, cited 36 times, exemplifies his work in translating neural principles into efficient robotic systems. This approach leverages asynchronous, event-based sensors to reduce computational load and latency, mimicking biological visual pathways. Benosmanz’s impact extends to advancing autonomous navigation, with applications in drones, autonomous vehicles, and prosthetics. His interdisciplinary efforts have earned him recognition as a leader in neuromorphic computing, inspiring students and researchers to explore how nature’s solutions can drive next-generation robotics and artificial intelligence.