Mohammad Ilyas Khan

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About

Mohammad Ilyas Khan is a leading researcher in the field of oxide-based resistive switching devices, with a primary focus on memristive technologies and their applications in neuromorphic computing and bio-inspired systems. His most-cited work, "Oxide-based resistive switching-based devices: fabrication, influence parameters and applications" (2021, 98 citations), presents a groundbreaking exploration of the nociceptor system in the human body and its artificial counterpart using memristor-based circuits. Khan’s major contribution lies in treating nociceptors as a practical material system within threshold switching-based devices, demonstrating how these artificial nociceptors can be integrated into robotic systems to mimic biological pain responses. This work bridges the gap between fundamental materials science and real-world robotics, offering a pathway toward more adaptive and intelligent machines. By investigating fabrication parameters and their influence on device performance, Khan has provided critical insights into optimizing resistive switching for reliable, scalable applications. His research not only advances the understanding of oxide-based devices but also paves the way for next-generation sensory systems in robotics, making him a key figure in the intersection of materials engineering and neuromorphic computing.