Wake Forest, NC, United States of America

Stewart T Sill


Average Co-Inventor Count = 7.0

ph-index = 1


Company Filing History:


Years Active: 2021

where 'Filed Patents' based on already Granted Patents

1 patent (USPTO):

Title: The Innovations of Stewart T Sill

Introduction

Stewart T Sill is a notable inventor based in Wake Forest, NC (US). He has made significant contributions to the field of technology, particularly in the area of machine learning and behavior modification. His innovative approach has led to the development of a unique patent that addresses user interventions based on behavioral data.

Latest Patents

Stewart T Sill holds a patent for a system titled "Personalized intervention based on machine learning of behavior change states." This system provides an intervention for users by utilizing at least one processor to monitor their behavior and context. It generates a behavior history and employs one or more models to determine effective interventions aimed at inducing behavior modification. The system not only delivers interventions but also receives feedback to refine its models, ensuring continuous improvement in user engagement and effectiveness.

Career Highlights

Stewart T Sill is associated with International Business Machines Corporation (IBM), where he has been instrumental in advancing research and development in machine learning applications. His work focuses on creating systems that enhance user experience through personalized interventions, showcasing his commitment to innovation in technology.

Collaborations

Stewart has collaborated with notable colleagues such as Marie Angelopoulos and Shahram Ebadollahi. Their combined expertise has contributed to the success of various projects within IBM, furthering advancements in the field of machine learning and behavior analysis.

Conclusion

Stewart T Sill's contributions to the field of technology through his innovative patent and collaborative efforts highlight his role as a leading inventor. His work continues to influence the development of personalized interventions, showcasing the potential of machine learning in behavior modification.

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