Shakopee, MN, United States of America

Sandeep Tikoo


Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2022

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1 patent (USPTO):Explore Patents

Title: Sandeep Tikoo: Innovator in High-Volume Transaction Queueing

Introduction

Sandeep Tikoo is an accomplished inventor based in Shakopee, MN (US). He has made significant contributions to the field of transaction processing through his innovative patent. His work focuses on enhancing the efficiency and reliability of ecommerce solutions.

Latest Patents

Sandeep Tikoo holds a patent for "High volume transaction queueing with machine learning." This invention is directed towards a system and method that provides a high-volume transaction queueing solution. It automatically engages and queues transactions when a primary back-end transaction processing system becomes unresponsive or unstable. The invention utilizes machine learning algorithms to control transaction submission rates by queuing them and throttling the rate at which they are processed. This is based on self-awareness, constant monitoring, feedback, and health checks of the primary system. When the metrics indicate that the third-party system can begin accepting transactions again, the system automatically feeds the queued transactions along with real-time orders at a manageable rate.

Career Highlights

Sandeep Tikoo is currently employed at Digital River, Inc., where he applies his expertise in transaction processing and machine learning. His innovative approach has positioned him as a key player in the development of advanced ecommerce solutions.

Collaborations

Sandeep has collaborated with notable professionals in his field, including Theodore Russell Cahall, Jr. and Ivan Atanasov Atanasov. These collaborations have further enriched his work and contributed to the success of his projects.

Conclusion

Sandeep Tikoo's contributions to high-volume transaction queueing demonstrate his commitment to innovation in the ecommerce sector. His patent reflects a significant advancement in transaction processing technology, showcasing the potential of machine learning in enhancing system reliability.

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