Wanying Ding

Title: Wanying Ding: Innovator in Knowledge Graphs and Graph Neural Networks

Introduction

Wanying Ding is a notable inventor based in Sunnyvale, CA, who has made significant contributions to the fields of knowledge graphs and graph neural networks. With a total of 2 patents, Wanying's work focuses on advanced techniques that leverage data structures to enhance decision-making processes in various applications.

Latest Patents

Wanying Ding's latest patents include "Systems and methods for leveraging a knowledge graph" and "Systems and methods for using graph neural networks for detecting competitors." The first patent describes a method that involves embedding a graph with an embedding model to generate node and edge vectors. This method also includes generating peer node groups, making edge predictions, and training a machine learning model to predict future actions based on these vectors. The insights generated are stored in an insight database, which is accessible through a user interface. The second patent outlines a method for using a graph neural network to predict competitors by analyzing datasets of supply chain companies, competitor companies, and customers. This method employs a first-order proximity to denote local connection structures and utilizes a pairwise ranking loss function to rank competitor companies based on their Euclidean distances in the graph.

Career Highlights

Wanying Ding is currently employed at JPMorgan Chase Bank, N.A., where he applies his expertise in graph technologies to drive innovation and improve competitive analysis. His work is instrumental in enhancing the bank's capabilities in data-driven decision-making.

Collaborations

Wanying collaborates with talented professionals such as Manoj Cherukumalli and Santosh Chikoti, contributing to a dynamic work environment that fosters innovation and creativity.

Conclusion

Wanying Ding's contributions to the fields of knowledge graphs and graph neural networks exemplify the impact of innovative thinking in technology. His patents reflect a commitment to advancing data analysis techniques, making him a valuable asset in the tech industry.