Fremont, CA, United States of America

Bijesh Rajamohanan

USPTO Granted Patents = 1 

Average Co-Inventor Count = 3.0

ph-index = 1

Forward Citations = 4(Granted Patents)


Company Filing History:


Years Active: 2017

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1 patent (USPTO):Explore Patents

Title: Innovations by Bijesh Rajamohanan in Reversible Resistance Memory Technology

Introduction

Bijesh Rajamohanan is an accomplished inventor based in Fremont, California. He has made significant contributions to the field of memory technology, particularly in the area of reversible resistance memory cells. His innovative work has led to the development of a patent that addresses key challenges in data storage.

Latest Patents

Bijesh Rajamohanan holds a patent for "Selecting reversible resistance memory cells based on initial resistance switching." This technology is designed to select a group of reversible-resistance memory cells for data storage based on their switching characteristics. The patent emphasizes the importance of understanding the transition from a first resistance state, immediately after fabrication, to a second resistance state. This insight is crucial for evaluating factors such as endurance and data retention. The control circuit described in the patent is configured to select memory cells based on the difficulty of switching states and the temperature of the data being stored.

Career Highlights

Bijesh Rajamohanan is currently employed at Western Digital Technologies, Inc., where he continues to advance his research in memory technologies. His work has positioned him as a key player in the development of innovative solutions for data storage challenges.

Collaborations

Some of his notable coworkers include Christopher John Petti and Xinde Hu. Their collaborative efforts contribute to the ongoing advancements in memory technology at Western Digital.

Conclusion

Bijesh Rajamohanan's contributions to reversible resistance memory technology highlight his innovative spirit and dedication to improving data storage solutions. His patent reflects a deep understanding of the complexities involved in memory cell performance, paving the way for future advancements in the field.

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