Austin, TX, United States of America

Randall M George


Average Co-Inventor Count = 4.4

ph-index = 2

Forward Citations = 79(Granted Patents)


Company Filing History:


Years Active: 2002-2025

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4 patents (USPTO):Explore Patents

Title: Innovations of Randall M George

Introduction

Randall M George is an accomplished inventor based in Austin, TX (US). He has made significant contributions to the field of technology, holding a total of 4 patents. His work primarily focuses on advancements in machine learning and interconnected environments.

Latest Patents

One of his latest patents is titled "Shiftleft topology construction and information augmentation using machine learning." This invention provides a method, a computer system, and a computer program product for constructing a shiftleft topology. The process includes collecting datasets, extracting topological entities, correlating data from these entities, mapping them, marking entry points for subgraphs, and ultimately constructing a topology graph.

Another notable patent is "Service issue source identification in an interconnected environment." This invention detects a first service's exhibition of a symptom while executing transactions. It constructs a graph representing data flow between services, evaluates the probability of a cause for the symptom, and identifies the problem service using the constructed candidate services.

Career Highlights

Randall M George is currently employed at International Business Machines Corporation, commonly known as IBM. His work at IBM has allowed him to explore innovative solutions and contribute to the advancement of technology.

Collaborations

He has collaborated with notable coworkers, including Brian Keith Howe and Stanley Allen Smith. Their combined expertise has fostered a creative environment that encourages innovation.

Conclusion

Randall M George's contributions to technology through his patents and collaborations highlight his role as a significant inventor in the field. His work continues to influence advancements in machine learning and interconnected systems.

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