Location History:
- Cedar Park, TX (US) (2006)
- Austin, TX (US) (2009 - 2010)
- Round Rock, TX (US) (2010 - 2011)
Company Filing History:
Years Active: 2006-2011
Title: Byron Christian Gehman: Innovator in Transaction Data Compression
Introduction
Byron Christian Gehman is a notable inventor based in Austin, TX (US). He has made significant contributions to the field of data processing, particularly in the area of transaction data compression. With a total of 5 patents to his name, Gehman continues to push the boundaries of technology through his innovative ideas.
Latest Patents
Gehman's latest patents include "Compress transaction data using serial micro-trends" and "Automatic configuration of robotic transaction playback through analysis of previously collected traffic patterns." The first patent focuses on compressing transaction data by determining whether a current data point is the first or subsequent point in a set. It also involves assessing if the subsequent data point falls within a predetermined tolerance of a predicted point, allowing for efficient data compression. The second patent outlines a system that automatically generates transaction playback scripts based on performance data from server applications, facilitating the execution of these scripts by robotic agents in geographical locales corresponding to client devices.
Career Highlights
Byron Gehman is currently employed at International Business Machines Corporation, commonly known as IBM. His work at IBM has allowed him to collaborate on various projects that enhance the efficiency of transaction processing and data management.
Collaborations
Some of Gehman's notable coworkers include Sandra Lee Tipton and Bryan Christopher Chagoly. Their collaborative efforts contribute to the innovative environment at IBM, fostering advancements in technology.
Conclusion
Byron Christian Gehman is a distinguished inventor whose work in transaction data compression and robotic transaction playback has made a significant impact in the tech industry. His contributions continue to shape the future of data processing and automation.