Shiva Nand Singh

National Institute of Technology Jamshedpur

Papers

Total Citations

146

H-Index

About

Shiva Nand Singh is a leading researcher in artificial intelligence and human-centered computing, whose work bridges deep learning and real-world applications. His most influential contribution is the "Inception inspired CNN-GRU hybrid network for human activity recognition" (2022), which has garnered 146 citations. This innovative model integrates convolutional neural networks with gated recurrent units, inspired by the Inception architecture, to achieve superior performance in recognizing complex human activities from sensor data. Singh’s research primarily focuses on developing efficient, hybrid deep learning architectures for time-series analysis, with applications in healthcare, smart environments, and wearable technology. His work stands out for its ability to capture both spatial and temporal dependencies, setting new benchmarks in activity recognition accuracy. Beyond this flagship paper, Singh has contributed to advancing interpretable AI and edge-computing solutions, making his models practical for deployment in resource-constrained devices. His achievements reflect a commitment to creating robust, scalable AI systems that enhance human-machine interaction. For students and researchers, Singh’s work exemplifies how combining classical neural network designs with modern recurrent structures can solve pressing challenges in ubiquitous computing.