معرفی
Hong Li is an Adjunct Professor at the University of Guelph, specializing in advanced deep learning techniques applied to medical imaging, computer vision, and edge computing. His research focuses on developing efficient neural network architectures for healthcare applications, sports analytics, and real-time systems.
Key research interests include designing compact networks like EdgeSegNet and EdgeSpeechNets for edge devices, developing explainable AI strategies, and applying deep learning to medical imaging for disease detection (e.g., COVID-19 via chest X-rays) and severity assessment. His work bridges theoretical advancements with practical deployment challenges in resource-constrained environments.
Publications highlight contributions to semantic segmentation, object tracking in sports (e.g., PuckNet for hockey puck localization), and neural architecture search methodologies. His research emphasizes interdisciplinary applications across healthcare, sports technology, and embedded systems.
