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About

Shavika Rastogi is pushing the boundaries of neuromorphic computing and bio-inspired sensing, with a focus on how machines can replicate the brain’s remarkable ability to process spatio-temporal patterns. Her landmark 2022 study on Braille letter reading established a rigorous benchmark for evaluating neuromorphic hardware, demonstrating how tactile pattern recognition—a task the brain performs effortlessly—can be achieved with far greater energy efficiency than conventional deep learning approaches. This work has garnered over 54 citations, reflecting its significance in the neuromorphic engineering community. More recently, in 2024, Rastogi turned to olfaction, developing a miniaturized electronic nose capable of high-speed odor sensing. Her system addresses a long-standing challenge in artificial olfaction: matching the millisecond-level recognition speeds of biological noses without sacrificing portability or affordability. With 53 citations already, this work promises to transform applications from environmental monitoring to medical diagnostics. Rastogi’s research elegantly bridges neuroscience, hardware design, and machine learning, offering practical pathways for deploying intelligent, low-power sensors in the real world.