Company Filing History:
Years Active: 2022-2025
Title: Innovations of Rajeshwari Ganesan
Introduction
Rajeshwari Ganesan is an accomplished inventor based in Palo Alto, California. She has made significant contributions to the field of machine learning and data transformation, holding a total of four patents. Her work focuses on developing innovative systems and methods that enhance the capabilities of machine learning models.
Latest Patents
One of her latest patents is titled "System and method for generating queries by machine learning models." This invention provides a method and system for generating queries based on data triggers. The machine learning model generates queries according to the corresponding domain and a knowledge graph. The model evolves the knowledge graph based on responses received in an encoded format. If the response does not culminate the current iteration, the model generates subsequent queries until the iteration is complete.
Another notable patent is the "Machine learning based method and system for transforming data." This method involves transforming data organized in a tabular structure. It includes assigning scores to cells within a table based on a set of orthogonal features, which encompass visual, syntactic, and language-based characteristics. The method identifies cell types and determines the overall table type, which can be row-oriented, column-oriented, or composite.
Career Highlights
Rajeshwari has worked with prominent companies such as Infosys Limited and Edgeverve Systems Limited. Her experience in these organizations has allowed her to refine her skills and contribute to various innovative projects.
Collaborations
Some of her notable coworkers include Megha Honna and Niraj Kunnumma. Their collaboration has likely fostered a creative environment that encourages innovation and the development of cutting-edge technologies.
Conclusion
Rajeshwari Ganesan's contributions to machine learning and data transformation are noteworthy. Her patents reflect her commitment to advancing technology and improving the efficiency of data processing systems. Her work continues to inspire future innovations in the field.