Munich, Germany

Radu Tudoran

USPTO Granted Patents = 3 

 

Average Co-Inventor Count = 5.5

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2022-2025

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3 patents (USPTO):Explore Patents

Title: Radu Tudoran: Innovator in Stream Processing and Anomaly Detection

Introduction

Radu Tudoran is a notable inventor based in Munich, Germany. He has made significant contributions to the fields of database management and anomaly detection. With a total of three patents to his name, Radu is recognized for his innovative approaches to complex technological challenges.

Latest Patents

Radu Tudoran's latest patents include a "System for embedding stream processing execution in a database." This invention describes a database management system that incorporates a storage mechanism for organizing data objects and stream operator wrappers. These wrappers facilitate the scheduling and deployment of stream operators, enhancing the efficiency of data processing.

Another significant patent is the "Device and method for anomaly detection on an input stream of events." This device is designed to detect anomalies in event streams by utilizing a modeling unit that represents events in a histogram format. It includes a change detection module to identify long-term changes in event distribution and a scoring unit to calculate the probability of anomalies.

Career Highlights

Radu is currently employed at Huawei Cloud Computing Technologies Co., Ltd., where he continues to develop innovative solutions in cloud computing and data management. His work has positioned him as a key player in the advancement of technology in these areas.

Collaborations

Radu collaborates with talented professionals such as Cristian Axenie and Stefano Bortoli. Their combined expertise fosters a creative environment that drives innovation and enhances project outcomes.

Conclusion

Radu Tudoran's contributions to stream processing and anomaly detection exemplify his commitment to innovation in technology. His patents reflect a deep understanding of complex systems and a dedication to improving data management practices.

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