Vamsi Krishna Potluru

Title: Vamsi Krishna Potluru: Innovator in Differential Privacy and Link Prediction

Introduction

Vamsi Krishna Potluru is a notable inventor based in New York, NY (US). He has made significant contributions to the fields of differential privacy and link prediction through his innovative patents. With a total of 3 patents, Potluru is recognized for his advanced methodologies that enhance data privacy and network analysis.

Latest Patents

Potluru's latest patents include a "Method and system for differentially private learning of Hawkes processes." This invention provides a method for preserving privacy while modeling event sequence data. The process involves receiving information about a sequence of events and modeling it using a Hawkes process. The method ensures that the accuracy of estimates corresponds to the observation time, while introducing differential privacy by adding noise to the event sequence.

Another significant patent is the "Method and system for link prediction in large multiplex networks." This invention utilizes a graph neural network framework to implement link prediction in a multiplex network environment. It identifies multiple layers of a multiplex network and employs a k-nearest approach to select layers for link prediction, enhancing the accuracy of network analysis.

Career Highlights

Vamsi Krishna Potluru is currently employed at JPMorgan Chase Bank, N.A., where he applies his expertise in data privacy and network analysis. His work at this prestigious financial institution allows him to contribute to innovative solutions that address complex challenges in the banking sector.

Collaborations

Potluru collaborates with talented professionals such as Mohsen Ghassemi and Eleonora Kreacic. These collaborations foster an environment of innovation and creativity, leading to the development of cutting-edge technologies.

Conclusion

Vamsi Krishna Potluru is a distinguished inventor whose work in differential privacy and link prediction has made a significant impact in his field. His contributions continue to advance the understanding and application of innovative methodologies in data analysis and privacy preservation.