Ke He

Ke He is a prolific researcher with over 15 publications between 2008 and 2025, focusing on machine learning, network security, and signal processing. His work spans multiple domains including Massive MIMO systems, hyperspectral imaging, network intrusion detection, and human-computer interaction through capacitive touchscreen research.

His recent publications highlight expertise in dynamic system modeling with applications to fractional-order financial risk systems and neurobiological models. He has pioneered graph-based intrusion detection techniques and 3D finger pose estimation methods. While his institutional affiliation isn't explicitly stated in the DBLP data, his collaborative work appears across institutions in China, Singapore, and Australia.

Ke He's research interests intersect mathematical modeling, deep learning, and system optimization. He has contributed to underwater acoustic signal processing, edge computing, and robust antenna selection algorithms. His work demonstrates consistent application of nonlinear dynamics and topological data analysis to practical engineering problems.