Dr. Hafiz Imtiaz

Human activity recognition (HAR) is crucial in applications such as smart homes, interactive games, surveillance, security, and healthcare. Channel State Information (CSI) data extracted from Wi-Fi signals has garnered significant interest for applications in HAR. We introduce a Differentially Private Principal Component-based Wavelet Convolutional Neural Network (DP-PCWCNN) that offers accurate and robust HAR performance across different environments, while preserving strict privacy constraints. This work led to this Springer Signal, Image and Video Processing publication.