Hanming Yan

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About

Hanming Yan is a leading researcher at the intersection of neuromorphic engineering and robotic perception, with a primary focus on spike-based neural coding and humanoid visual systems. Yan’s work addresses fundamental bottlenecks in artificial tactile perception by pioneering event-driven, spike-based architectures that bypass the energy and latency constraints of traditional von Neumann computing—a contribution that has garnered 6 citations in just one year. In parallel, Yan has advanced the field of humanoid robotics through comprehensive surveys on visual perception, synthesizing breakthroughs that enable robots to interpret complex environments for applications in healthcare and manufacturing. With 5 citations for this survey, Yan’s synthesis of cutting-edge techniques has become a key reference for researchers aiming to enhance robotic autonomy. Notably, Yan’s recent 2025 paper on tactile perception is already shaping the next generation of neuromorphic sensors, promising ultra-efficient, real-time feedback for prosthetic and robotic systems. Through these contributions, Yan is driving a paradigm shift toward biologically inspired computing, making robots more responsive, energy-efficient, and capable of nuanced interaction with the physical world.