Austin, TX, United States of America

Andrew Kraemer

USPTO Granted Patents = 2 

Average Co-Inventor Count = 7.0

ph-index = 1

Forward Citations = 22(Granted Patents)


Company Filing History:


Years Active: 2019-2022

where 'Filed Patents' based on already Granted Patents

2 patents (USPTO):

Title: The Innovations of Andrew Kraemer

Introduction

Andrew Kraemer is an accomplished inventor based in Austin, TX. He has made significant contributions to the field of machine learning, holding two patents that showcase his innovative approach to behavior-dependent processes. His work is instrumental in advancing the capabilities of artificial intelligence.

Latest Patents

Kraemer's latest patents include "Machine-learning models to leverage behavior-dependent processes" and "Multi-stage machine-learning models to control path-dependent processes." The first patent outlines a process that involves obtaining a first training dataset of subject-entity records, training a first machine-learning model on this dataset, and forming virtual subject-entity records. This process culminates in training a second machine-learning model on a newly created dataset. The second patent follows a similar structure, emphasizing the importance of multi-stage models in controlling complex processes.

Career Highlights

Andrew Kraemer is currently employed at Cerebri AI Inc., where he applies his expertise in machine learning to develop innovative solutions. His work at the company reflects his commitment to pushing the boundaries of technology and enhancing the efficiency of machine learning applications.

Collaborations

Kraemer collaborates with notable colleagues such as Gabriel M Silberman and Alain Briançon. These partnerships contribute to a dynamic work environment that fosters creativity and innovation.

Conclusion

Andrew Kraemer's contributions to machine learning and his innovative patents position him as a key figure in the field. His work continues to influence the development of advanced technologies that leverage behavioral data for improved outcomes.

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