This inventor holds 1 USPTO granted patent and 2 published patent applications. Top assignee: Optum Services (Ireland) Limited. Active years: 2026.
Company Filing History:
Years Active: 2026
Title: Arjit Agrawal: Innovator in Predictive Machine Learning
Introduction
Arjit Agrawal is a prominent inventor based in Dublin, Ireland. He has made significant contributions to the field of machine learning, particularly in feature selection techniques. His innovative approach aims to enhance the development, performance, and maintenance of machine learning models.
Latest Patents
Arjit Agrawal holds a patent for a predictive machine learning feature selection. This patent encompasses various embodiments that provide feature engineering techniques to improve machine learning model development. The techniques include generating a model description vector from a textual model description for a target machine learning model. Additionally, it involves using this vector to create description-based similarity vectors that contain similarity scores for various machine learning features. The patent also details the generation of a label-based similarity vector, which compares training data for the target model with feature values. Ultimately, these techniques provide a predictive feature set for the target machine learning model based on the generated similarity vectors.
Career Highlights
Arjit Agrawal is currently employed at Optum Services (Ireland) Limited, where he applies his expertise in machine learning. His work focuses on developing advanced algorithms that enhance the efficiency and accuracy of predictive models. His innovative contributions have positioned him as a key player in the field of machine learning.
Collaborations
Arjit has collaborated with notable colleagues, including Karim M Mahmoud Mohamed Moustafa and Eugene Edward Farrell. These collaborations have fostered a dynamic environment for innovation and have led to the development of cutting-edge solutions in machine learning.
Conclusion
Arjit Agrawal's work in predictive machine learning feature selection exemplifies his commitment to advancing technology in this field. His innovative techniques and collaborations continue to influence the development of more efficient machine learning models.