Jiang Wan

Title: Jiang Wan: Innovator in Graph Convolutional Neural Networks and Cyber-Physical Manufacturing

Introduction

Jiang Wan is a prominent inventor based in Irvine, CA, known for his contributions to the fields of artificial intelligence and cyber-physical systems. With a total of 5 patents, he has made significant strides in developing innovative methodologies that enhance the understanding and functionality of complex systems.

Latest Patents

One of Jiang Wan's latest patents is titled "SGCNN: Structural Graph Convolutional Neural Network." This invention presents a computer-implemented method for learning structural relationships between nodes of a graph. The process involves generating a knowledge graph that comprises nodes representing a system and applying a graph-based convolutional neural network (GCNN) to this knowledge graph. The GCNN includes several layers, such as a graph feature compression layer, a neighbor nodes aggregation layer, and a subgraph convolution layer, all designed to generate feature vectors that describe the structural relationships between the nodes.

Another notable patent is "Information Leakage-Aware Computer Aided Cyber-Physical Manufacturing." This methodology allows cyber-domain tools, such as computer-aided manufacturing (CAM), to be aware of existing information leakage. By adjusting machine processes or product design parameters in the cyber-domain, the methodology aims to minimize information leakage, thereby enhancing security across both cyber and physical domains.

Career Highlights

Jiang Wan has worked with esteemed organizations, including the University of California and Siemens Aktiengesellschaft. His experience in these institutions has allowed him to collaborate on various innovative projects that bridge the gap between theoretical research and practical applications.

Collaborations

Throughout his career, Jiang has collaborated with notable professionals, including Mohammad Abdullah Al Faruque and Sujit Rokka Chhetri. These collaborations have contributed to the advancement of his research and the successful development of his patented technologies.

Conclusion

Jiang Wan's innovative work in graph convolutional neural networks and cyber-physical manufacturing showcases his commitment to advancing technology and enhancing system security. His contributions continue to influence the fields of artificial intelligence and manufacturing, making him a significant figure in contemporary innovation.