Ke Zhao

Ke Zhao is a prolific researcher with extensive contributions in interdisciplinary domains spanning computer science, mechanical engineering, biomedical engineering, and neuroscience. His work focuses on advanced machine learning techniques applied to fault diagnosis, medical imaging analysis, and real-world systems optimization. Key areas of expertise include federated learning, domain adaptation, and deep learning for industrial and healthcare applications.

• Primary research themes: Fault diagnosis in rotating machinery, computer vision for satellite imagery, and neural network applications in healthcare.
• Collaborations with institutions globally on projects involving edge computing, battery management systems, and genetic status prediction in gliomas.

Recent advancements include breakthroughs in federated domain adaptation frameworks for gearbox fault detection and immersive VR systems for cultural empathy. His work bridges theoretical machine learning with practical engineering solutions.