Shanghai, China

Haoran Zhang

USPTO Granted Patents = 5 

Average Co-Inventor Count = 10.0

ph-index = 1

Forward Citations = 3(Granted Patents)


Company Filing History:


Years Active: 2022-2025

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5 patents (USPTO):

Title: Haoran Zhang: Innovator in Graph Computing and Machine Learning

Introduction

Haoran Zhang is a prominent inventor based in Shanghai, China, known for his contributions to the fields of graph computing and machine learning. With a total of four patents to his name, Zhang has made significant strides in enhancing electronic communication security and improving machine learning model efficiency.

Latest Patents

Zhang's latest patents include innovative techniques for detecting risks in electronic communications. One of his notable inventions involves a server system that identifies potential risks based on user activity. This system executes computations to assess the communication's safety before it is initiated, thereby reducing the likelihood of unsecure electronic communications. Another significant patent focuses on graph-based feature engineering for machine learning models. This invention assists users in identifying and evaluating features for machine learning tasks by utilizing graph data structures, ultimately enhancing the model's performance.

Career Highlights

Haoran Zhang is currently employed at PayPal, Inc., where he applies his expertise in technology and innovation. His work at PayPal has allowed him to contribute to advancements in secure electronic transactions and machine learning applications.

Collaborations

Zhang collaborates with talented individuals in his field, including coworkers Junshi Guo and Pengshan Zhang. Their combined efforts foster a creative environment that drives innovation and technological progress.

Conclusion

Haoran Zhang's contributions to graph computing and machine learning exemplify the impact of innovative thinking in technology. His patents not only enhance electronic communication security but also improve the efficiency of machine learning models.

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