Morristown, NJ, United States of America

Vivek Kumar Rangarajan Sridhar

This inventor holds 16 USPTO granted patents and 3 published patent applications. Top assignees: At&t Intellectual Property I, LP, Nuance Communications, Inc.. Active years: 2011-2022.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Vivek Kumar Rangarajan Sridhar. Retrieved from https://idiyas.com/inventor/vivek-kumar-rangarajan-sridhar

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

USPTO Granted Patents = 16 

% Patents Active = 50.0

Average Co-Inventor Count = 1.5

ph-index = 5

Forward Citations = 64(Granted Patents)


Location History:

  • Goleta, CA (US) (2011 - 2016)
  • Florham Park, NJ (US) (2016 - 2018)
  • Morristown, NJ (US) (2017 - 2022)

Company Filing History:


Years Active: 2011-2022

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16 patents (USPTO):Explore Patents

Title: Innovations of Vivek Kumar Rangarajan Sridhar

Introduction

Vivek Kumar Rangarajan Sridhar is an accomplished inventor based in Morristown, NJ (US). He holds a total of 16 patents that showcase his expertise in the field of technology and innovation. His work primarily focuses on advancements in text normalization and topic modeling.

Latest Patents

One of his latest patents is titled "System and method for unsupervised text normalization using distributed representation of words." This invention provides a system and method for the unsupervised normalization of noisy text by utilizing a distributed representation of words. The system receives a word with a non-canonical spelling from a social media forum and determines its context. It identifies the word in a vector space model and selects 'n-best' vector paths based on the context and the non-canonical spelling. Ultimately, it identifies a canonical version of the word based on a similarity cost.

Another significant patent is "Unsupervised topic modeling for short texts." This invention determines topics for short text messages using an unsupervised topic model. A training corpus is created from various short text messages, and a vocabulary of words is identified. Each word is processed to obtain a distributed vector representation. The corpus is modeled as a Gaussian mixture model, where Gaussian components represent different topics. The system can then determine the topic of a sample short text message using this model.

Career Highlights

Vivek has worked with notable companies such as AT&T Intellectual Property L.P. and Nuance Communications, Inc. His contributions to these organizations have significantly advanced their technological capabilities.

Collaborations

Some of his coworkers include Srinivas Bangalore and David James Thomson. Their collaboration has likely contributed to the innovative projects that Vivek has been involved in.

Conclusion

Vivek Kumar Rangarajan Sridhar is a prominent inventor whose work in text normalization and topic modeling has made a significant impact in the field of technology. His numerous patents reflect his dedication to innovation and advancement.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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