Long Island City, NY, United States of America

Reka Daniel-Weiner


Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2023

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1 patent (USPTO):Explore Patents

Title: Reka Daniel-Weiner: Innovator in Unsupervised Machine Learning

Introduction

Reka Daniel-Weiner is a notable inventor based in Long Island City, NY (US). She has made significant contributions to the field of machine learning, particularly in the area of audience identification and behavioral data analysis. Her innovative approach has led to the development of a unique patent that enhances the understanding of user behavior.

Latest Patents

Reka holds a patent for "Unsupervised machine learning for identification of audience subpopulations and dimensionality and/or sparseness reduction techniques to facilitate identification of audience subpopulations." This patent describes a computer-implemented method that involves accessing behavioral data, such as web visitation data, from multiple users. The method defines a sparse behavioral vector for each user, encoding their behavioral data. By applying multiple supervised learning models, the vectors are densified, allowing for the application of unsupervised machine learning techniques to cluster users into subpopulations based on similarities. This innovation facilitates the delivery of targeted content to users based on their behavioral profiles.

Career Highlights

Reka is currently employed at Dstillery, Inc., where she continues to advance her research and development in machine learning technologies. Her work has positioned her as a key player in the field, contributing to the evolution of data-driven marketing strategies.

Collaborations

Reka collaborates with talented individuals such as Melinda Han Williams and Amelia Grieve White. These partnerships enhance her research efforts and contribute to the innovative environment at Dstillery, Inc.

Conclusion

Reka Daniel-Weiner's contributions to unsupervised machine learning and audience identification demonstrate her commitment to innovation in technology. Her patent reflects a significant advancement in understanding user behavior, paving the way for more effective data utilization in marketing.

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