Qu, Weihao

Abstract This work aims to find more promising sources of data from various aspects in improving tennis players’ performance and injury prediction. The diverse sources of data in this work are collected from nine collegiate tennis players, including physiological metrics, training and match data, sleep data from wearable devices, self-reported information via daily questionnaires, jump assessments conducted by experts, and videos of match play. Accordingly, this work proposes a multimodal...

Abstract AI-driven phishing, spoofing, and deepfake attacks pose escalating risks across email systems, educational platforms, and digital social spaces. Publicly available tools now enable adversaries to generate convincing impersonations, bypass conventional defenses, and exploit human trust through email spoofing, voice cloning, and real-time face swapping. These threats highlight the limitations of traditional security awareness training and automated filters when faced with adaptive,...