Anju P. Johnson

Intelligent Systems Research (United States), University of York, University of Ulster

Papers

Total Citations

116

H-Index

About

Anju P. Johnson is a leading researcher at the intersection of neuromorphic computing and fault-tolerant hardware, whose work draws profound inspiration from the self-repair mechanisms of the biological brain. Her primary research areas include spiking neural networks (SNNs), astrocyte-neural networks, and hardware fault tolerance, particularly on Field Programmable Gate Arrays (FPGAs). Johnson’s major contribution is pioneering the concept of "homeostatic fault tolerance," demonstrating how neural plasticity can be harnessed to create electronic systems that dynamically self-repair. Her seminal 2017 paper, with 58 citations, established a foundational plastic neural network model that maintains stability (homeostasis) in SNNs under duress. She further advanced the field by integrating astrocyte cells—biological glial cells—into neural networks, as shown in her 2018 work (50 citations), which demonstrated localized self-repair via retrograde signaling. Johnson’s impact is evident in her highly cited foundational papers, which have shaped research into bio-inspired resilience. Her notable achievement includes developing a fault-tolerant learning rule combining STDP and BCM on FPGA hardware, a practical step toward robust neuromorphic systems. For students and researchers, Johnson’s work offers a compelling vision: building electronic brains that heal themselves, just as our own do.