معرفی
Haimin Zhang is a Research Fellow at the School of Electrical and Data Engineering, University of Technology Sydney (UTS). He holds a PhD in Computer Science from UTS (2015–2019) and specializes in computer vision, machine learning, and pattern recognition. His research focuses on advancing techniques in graph neural networks, adversarial machine learning, emotion recognition, and multimodal data fusion. Dr. Zhang actively collaborates on projects involving WiFi-based human tracking, personalized AI search engines, and retrieval-augmented language models.
Education:
- PhD in Computer Science, University of Technology Sydney, 2015–2019
Research interests span computer vision applications like face alignment and style transfer, as well as foundational machine learning topics such as graph representation learning and unsupervised feature discovery. His work bridges theoretical advancements with practical systems, including vital sign monitoring via mmWave radar-camera fusion and high-order feature interaction models for click-through rate prediction.
His recent publications (2023–2025) emphasize cross-domain dataset alignment, efficient retrieval-augmented generation systems, and regularization techniques for graph neural networks. He is available to supervise master’s and PhD students in these domains.