This inventor holds 2 USPTO granted patents and 1 EPO patent. Top assignee: Tata Consultancy Services Limited. Active years: 2025.
Company Filing History:
Years Active: 2025
Title: Neha Behl: Innovator in Batch Process Prediction
Introduction
Neha Behl is a prominent inventor based in Pune, India. He has made significant contributions to the field of batch process prediction, holding 2 patents that address critical challenges in data accuracy and efficiency.
Latest Patents
Neha's latest patents include "Enhancing batch predictions by localizing jobs contributing to time deviation and generating fix recommendations." This invention focuses on analyzing data inaccuracy and insufficiency to improve batch predictions, particularly in the context of Service Level Agreement (SLA) jobs. The method provides a system for localizing jobs that contribute to time deviations and generating effective fix recommendations. By traversing a batch graph, the system identifies the real contributors to inaccuracies, enabling root cause analysis and enhancing prediction accuracy.
Another notable patent is the "Method and system for predicting batch processes." This invention outlines a method for generating batch graphs and models from user-defined batch jobs. It includes forecasting and regression models to predict revised batch job schedules in real-time. The system also proactively notifies users of unexpected delays, ensuring better management of batch processes.
Career Highlights
Neha Behl is currently employed at Tata Consultancy Services Limited, where he applies his expertise in batch process prediction. His work has significantly impacted the efficiency of batch job scheduling and execution in distributed networks.
Collaborations
Neha collaborates with talented coworkers, including Vikrant Vikas Shimpi and Maitreya Natu, to further enhance the innovations in batch processing.
Conclusion
Neha Behl is a distinguished inventor whose work in batch process prediction has led to valuable advancements in the field. His patents reflect a commitment to improving data accuracy and efficiency in batch processing systems.
