This inventor holds 1 USPTO granted patent. Top assignee: S&p Global Inc.. Active years: 2026.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2026
Title: Anubhav Agarwal: Innovator in Machine Learning Platforms
Introduction
Anubhav Agarwal is a notable inventor based in Brooklyn, NY (US). He has made significant contributions to the field of machine learning through his innovative patent. His work focuses on enhancing data modeling and visualization in multi-tenant environments.
Latest Patents
Anubhav holds a patent for a "Dynamic multi-tenant data platform for machine learning modeling and visualization." This invention encompasses a method, apparatus, system, and computer program code designed for dynamically modeling multi-tenant data within a machine learning platform. The recommendation engine he developed receives a first data set from a user and characterizes it to determine its attributes and characteristics. It aligns these attributes with a second data set according to an ontology. Based on the characteristics of the first data set, the engine identifies a set of pre-trained models that were trained using parameters selected from the second data set. Ultimately, it recommends these models to the user, enhancing the efficiency of machine learning applications.
Career Highlights
Anubhav is currently employed at S&P Global Inc., where he continues to innovate and contribute to advancements in data platforms. His expertise in machine learning and data analysis has positioned him as a valuable asset in his field.
Collaborations
Anubhav collaborates with talented professionals such as Stanley Guzik and Prashant Desai, further enriching his work environment and fostering innovation.
Conclusion
Anubhav Agarwal's contributions to machine learning through his patent demonstrate his commitment to advancing technology in data modeling and visualization. His work not only enhances the capabilities of machine learning platforms but also sets a foundation for future innovations in the field.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile