Joydeep Basu

Papers

Total Citations

117

H-Index

About

Joydeep Basu is a leading figure in neuromorphic engineering and bioinspired robotics, whose work redefines how sensory information is processed in artificial systems. His research centers on developing self-healable, decentralized sensory architectures that mimic biological neural networks, enabling robots to process tactile and environmental signals directly on their "skins" rather than relying on centralized processors. His most-cited work, a 2020 study on self-healable neuromorphic memtransistor elements for decentralized sensory signal processing in robotics, has garnered 117 citations and demonstrates a breakthrough in reducing wiring complexity and data transfer bottlenecks by integrating computation with sensing. This innovation holds profound implications for soft robotics, prosthetics, and human-machine interfaces, where resilience and real-time processing are critical. Basu’s contributions bridge materials science, device physics, and robotics, offering a paradigm shift toward autonomous, adaptive systems that can heal and learn from their environment. His achievements have positioned him as a key architect of next-generation intelligent machines, inspiring researchers to rethink the boundaries between body and brain in artificial systems.