Redwood City, CA, United States of America

Shahriar Shariat


Average Co-Inventor Count = 4.5

ph-index = 2

Forward Citations = 12(Granted Patents)


Company Filing History:


Years Active: 2018-2019

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2 patents (USPTO):Explore Patents

Title: Shahriar Shariat: Innovator in Machine Learning and User Identification

Introduction

Shahriar Shariat is a notable inventor based in Redwood City, CA. He has made significant contributions to the fields of machine learning and user identification, holding a total of 2 patents. His work focuses on enhancing the efficiency of machine-learned models and improving online user targeting.

Latest Patents

Shariat's latest patents include "Selective distribution of machine-learned models" and "Methods and apparatus for identifying a cookie-less user." The first patent describes a system where machine-learned models are selectively distributed to multiple computer servers based on specific conditions. This innovative approach allows servers to receive travel information from a coordination system, identify hierarchies of conditions, and train models accordingly. The second patent outlines methods for identifying online users for targeted advertisements or content. It involves obtaining historical user data and selecting user identifiers based on fingerprint vectors associated with specific users.

Career Highlights

Throughout his career, Shahriar has worked with prominent companies such as Uber Technologies, Inc. and Amobee, Inc. His experience in these organizations has allowed him to refine his skills and contribute to groundbreaking projects in technology and user experience.

Collaborations

Shahriar has collaborated with talented individuals in his field, including Pusheng Zhang and Brandon White. These partnerships have fostered innovation and have been instrumental in the development of his patented technologies.

Conclusion

Shahriar Shariat is a distinguished inventor whose work in machine learning and user identification continues to impact the technology landscape. His patents reflect a commitment to advancing the efficiency of machine-learned models and enhancing user targeting strategies.

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