Papers
2
Total Citations
76
H-Index
2
About
Deepak Baby is a researcher whose work spans the intersection of computational neuroscience, signal processing, and artificial intelligence applications in healthcare. His most influential contribution, a 2021 paper on convolutional neural network modeling of human cochlear mechanics, has garnered 61 citations and represents a significant advancement in auditory processing research. By developing a real-time computational model of cochlear mechanics and filter tuning, Baby bridges the gap between biological hearing systems and machine learning architectures, with implications for hearing aid technology, speech processing, and auditory modeling. His research demonstrates a sophisticated understanding of how the human auditory system processes sound, translating complex biomechanical processes into efficient neural network frameworks suitable for practical applications. Beyond auditory science, Baby has also contributed to the exploration of artificial intelligence in dental education, examining how Indian dentists perceive and understand AI and robotics in oral healthcare — a study that reflects his broader interest in AI adoption within clinical settings. With a growing citation record across diverse domains, Baby exemplifies a versatile researcher committed to applying computational intelligence to real-world biomedical challenges, making his work valuable to students and professionals in both engineering and healthcare fields.
Research Focus
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Top Papers
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