SeyedMohsen Jamali

Title: SeyedMohsen Jamali: Innovator in Machine Learning and Content Relevance

Introduction

SeyedMohsen Jamali is a prominent inventor based in Sunnyvale, CA. He has made significant contributions to the field of machine learning and content relevance, holding a total of 4 patents. His work focuses on enhancing the way content is predicted and engaged with in digital environments.

Latest Patents

One of his latest patents is titled "Embedded learning for response prediction in content item relevance." This patent outlines techniques for utilizing machine learning to learn embeddings for content items. The process involves training data to learn embeddings for various attribute values of multiple content items and entities. It also includes identifying a content item based on targeting criteria that align with a content request. Another notable patent is "Using online engagement footprints for video engagement prediction." This patent describes methods for predicting video engagement by analyzing events from multiple client devices. It employs machine learning techniques to train a prediction model based on engagement events and features.

Career Highlights

SeyedMohsen Jamali is currently employed at Microsoft Technology Licensing, LLC, where he continues to innovate in the realm of technology and machine learning. His work has been instrumental in developing advanced techniques that improve content relevance and user engagement.

Collaborations

He collaborates with talented individuals such as Samaneh Abbasi Moghaddam and Revant Kumar, contributing to a dynamic and innovative work environment.

Conclusion

SeyedMohsen Jamali's contributions to machine learning and content relevance are noteworthy. His patents reflect a deep understanding of technology and its application in enhancing user experiences. His ongoing work at Microsoft Technology Licensing, LLC positions him as a key player in the field of innovation.