Mayuresh Hooli

Title: Mayuresh Hooli: Innovator in Machine Learning for Communications Networks

Introduction

Mayuresh Hooli is a prominent inventor based in Dallas, TX (US). He has made significant contributions to the field of machine learning, particularly in optimizing model performance within communications networks. His innovative approach has led to the development of a unique patent that addresses key challenges in this area.

Latest Patents

Mayuresh Hooli holds a patent titled "System and method for improving machine learning model performance in a communications network." This patent describes a system, method, and non-transitory computer-readable media for optimizing input data for a machine learning model associated with a communications network. In one implementation, the machine learning model(s) may be trained using a modified dataset obtained from a plurality of cellular aggregation units (CAUs) of the Radio Access Network (RAN) infrastructure(s). The modified dataset is derived from data collected for individual CAUs over a data collection period concerning a plurality of Key Performance Indicator (KPI) variables. The dataset is optimized by replacing null values of variables with corresponding modal values. The trained machine learning model can then be used to predict one or more KPIs based on a set of test data associated with the RAN infrastructure(s). He has 1 patent to his name.

Career Highlights

Mayuresh Hooli is currently employed at Telefonaktiebolaget LM Ericsson (Publ), a leading company in telecommunications and networking. His work focuses on enhancing machine learning applications to improve network performance and efficiency. His expertise in this domain has positioned him as a valuable asset to his organization.

Collaborations

Some of his notable coworkers include Miroslav Budic and Pulin Chhatbar. Their collaborative efforts contribute to the advancement of innovative solutions in the telecommunications sector.

Conclusion

Mayuresh Hooli is a distinguished inventor whose work in machine learning has the potential to revolutionize communications networks. His patent reflects a commitment to improving technology and optimizing performance in this critical field.