Austin, TX, United States of America

Sankalp Acharya


Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2020-2021

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2 patents (USPTO):Explore Patents

Title: Innovations by Sankalp Acharya

Introduction

Sankalp Acharya is an accomplished inventor based in Austin, TX. He has made significant contributions to the field of technology, particularly in the area of machine learning and geolocation prediction. With a total of 2 patents, his work showcases innovative approaches to complex event processing.

Latest Patents

Sankalp's latest patents focus on scalable complex event processing using probabilistic machine learning models to predict subsequent geolocations. The process involves obtaining a set of historical geolocations and segmenting them into multiple temporal bins. He determines pairwise transition probabilities between various geographic places based on these historical geolocations. Furthermore, he configures a compute cluster by assigning subsets of the transition probabilities to different computing devices. The system receives a geolocation stream that indicates the current locations of individuals. It then selects a computing device in the cluster that contains the relevant transition probabilities for the received geolocation. Finally, it predicts a subsequent geographic place based on the selected transition probabilities.

Career Highlights

Sankalp Acharya is currently employed at RetailMeNot, Inc., where he continues to innovate and develop new technologies. His work has been instrumental in enhancing the capabilities of event processing systems.

Collaborations

Sankalp collaborates with talented individuals such as David John Reese and Annette M Taberner-Miller, contributing to a dynamic and innovative work environment.

Conclusion

Sankalp Acharya's contributions to the field of technology through his patents and work at RetailMeNot, Inc. highlight his role as a forward-thinking inventor. His innovative approaches to machine learning and geolocation prediction are paving the way for future advancements in the industry.

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