Los Angeles, CA, United States of America

Saurav Prakash

USPTO Granted Patents = 3 

Average Co-Inventor Count = 5.0

ph-index = 2

Forward Citations = 14(Granted Patents)


Company Filing History:


Years Active: 2022-2024

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3 patents (USPTO):Explore Patents

Title: Innovations by Saurav Prakash in Machine Learning Technologies

Introduction

Saurav Prakash is an accomplished inventor based in Los Angeles, CA. He has made significant contributions to the field of machine learning and computing technologies. With a total of three patents to his name, Prakash is recognized for his innovative approaches to distributed machine learning.

Latest Patents

Prakash's latest patents focus on technologies for distributing gradient descent computation in heterogeneous multi-access edge computing (MEC) networks. These systems, apparatuses, methods, and computer-readable media are designed for distributed machine learning training using heterogeneous compute nodes. The nodes are connected to a master node via respective wireless links. Individual heterogeneous compute nodes perform machine learning computations on their respective training datasets, while the master node combines the outputs of these computations. The balancing of ML computations across the nodes is based on network conditions and operational constraints.

Another notable patent by Prakash involves technologies for distributing iterative computations in heterogeneous computing environments. This patent outlines systems, apparatuses, methods, and computer-readable media for load partitioning in distributed machine learning training. Similar to his previous work, this technology utilizes heterogeneous compute nodes connected to a master node via wireless links. The computations are balanced based on the computational and link parameters of the nodes.

Career Highlights

Saurav Prakash is currently employed at Intel Corporation, where he continues to develop innovative solutions in the field of machine learning. His work has garnered attention for its practical applications in enhancing computational efficiency and performance in heterogeneous environments.

Collaborations

Prakash collaborates with talented individuals such as Sagar Dhakal and Yair Yona, contributing to a dynamic and innovative work environment.

Conclusion

Saurav Prakash's contributions to machine learning technologies demonstrate his commitment to advancing the field through innovative solutions. His patents reflect a deep understanding of the complexities involved in distributed computing and machine learning.

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