Company Filing History:
Years Active: 2023-2024
Title: Sphoorthy Pamaraju: Innovator in Data Processing Technologies
Introduction
Sphoorthy Pamaraju is a talented inventor based in Secaucus, NJ (US). She has made significant contributions to the field of data processing and machine learning. With a focus on enriching and normalizing data, her work has the potential to transform how organizations handle and analyze information.
Latest Patents
Sphoorthy holds 2 patents that showcase her innovative approach. Her latest patent is a system and method for enriching and normalizing data. This integrated platform employs a series of machine learning techniques and prediction and detection units that can process input data and extract and generate meaningful insights and predictions. The system integrates multiple different data storage types and applications that generate various data types. It includes an associated processing system for processing these different data types, storing the data in a common data model to normalize it, determining the data lineage, and processing the data using various techniques. Additionally, the data can be processed by a prediction unit for generating insights or by an anomaly detection unit for identifying anomalies in the data.
Career Highlights
Sphoorthy is currently employed at KPMG LLP, where she continues to develop her expertise in data processing technologies. Her work at KPMG allows her to collaborate with other professionals in the field and contribute to innovative projects that leverage her patented technologies.
Collaborations
Some of her notable coworkers include Niels Hanson and James Johnson Gardner. Their collaboration fosters a creative environment that encourages the development of cutting-edge solutions in data processing.
Conclusion
Sphoorthy Pamaraju is a remarkable inventor whose work in data processing and machine learning is paving the way for advancements in the field. Her patents reflect her commitment to innovation and her ability to create systems that enhance data analysis.