Santa Clara, CA, United States of America

Mostafa Rahmani


Average Co-Inventor Count = 11.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2024

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1 patent (USPTO):

Title: Mostafa Rahmani: Innovator in Anomaly Detection

Introduction

Mostafa Rahmani, based in Santa Clara, California, is an accomplished inventor known for his work in anomaly detection systems. His innovative approach to detecting potential anomalies has led to the grant of a patent, showcasing his contributions to technology and data analysis.

Latest Patents

Rahmani holds a singular patent titled "Anomaly Detection Using Feedback." This patent details advanced techniques for performing anomaly detection, which involve several steps: receiving a request for anomaly detection, processing data to score it against predefined thresholds, soliciting feedback on identified anomalies, and adjusting thresholds accordingly without modifying the underlying anomaly scoring model. This method represents a significant advancement in the precision and adaptability of anomaly detection systems.

Career Highlights

Currently employed at Amazon Technologies, Inc., Mostafa Rahmani has established himself as a vital contributor to innovation within the company. His expertise in developing sophisticated anomaly detection systems demonstrates his ability to apply theoretical knowledge to practical applications in technology.

Collaborations

In his career, Rahmani has had the opportunity to collaborate with industry professionals, including his coworker Laurent Callot, enhancing the scope of their projects through shared insights and collective expertise. These collaborations have undoubtedly played a role in the successful development and implementation of his patented techniques.

Conclusion

Mostafa Rahmani exemplifies the spirit of innovation through his work in anomaly detection at Amazon Technologies, Inc. His patent highlights not only his ingenuity but also the ongoing evolution of technology in interpreting complex data. As the field of anomaly detection continues to grow, Rahmani's contributions are sure to pave the way for future advancements and applications.

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