Menglan Hu

Huazhong University of Science and Technology

Papers

Total Citations

139

H-Index

About

Menglan Hu is a leading researcher at the intersection of artificial intelligence and the Internet of Things (IoT). His work primarily focuses on deep learning for IoT applications and advanced signal processing for sound source localization. Hu’s major contributions include a landmark survey on deep learning-empowered IoT applications, which has garnered 124 citations and serves as a foundational reference for researchers integrating AI with connected devices. This work systematically maps how deep neural networks can address key IoT challenges, from data analytics to security. In the domain of acoustic sensing, Hu developed novel approaches for robust multiple blind sound source localization, combining source separation and beamforming techniques to overcome the traditional limitations of microphone arrays. His 2021 paper on this topic (15 citations) demonstrates how to locate multiple simultaneous sound sources—a critical capability for robotic navigation and indoor positioning systems. Hu’s research is notable for bridging theoretical advances with practical deployment challenges, making his work highly cited by both academic researchers and industry practitioners working on smart environments and autonomous systems.