Company Filing History:
Years Active: 2025
Title: Prasiddha Malla: Innovator in Machine Learning Applications
Introduction
Prasiddha Malla is an accomplished inventor based in Milpitas, CA. He has made significant contributions to the field of machine learning, particularly in predicting outcomes of prospective transactions. His innovative approach leverages historical data to enhance decision-making processes.
Latest Patents
Prasiddha holds a patent for a method titled "Training and using a two stage machine learning model to predict an outcome of a prospective transaction." This patent describes a machine learning model, such as a Gradient Boosting Machine model, that is trained using historical data associated with various operations. The model extracts features from this data to learn which factors lead to specific outcomes, such as approval by a designated entity. Once trained and validated for accuracy, the model predicts the likelihood of a prospective operation achieving the desired outcome when submitted immediately versus at a later date. If the immediate submission is deemed unlikely to succeed, the model suggests a future submission time that increases the chances of approval. This innovative approach minimizes the waste of electronic resources, including computer processing power and network bandwidth.
Career Highlights
Prasiddha Malla is currently employed at PayPal, Inc., where he applies his expertise in machine learning to improve transaction processes. His work is instrumental in enhancing the efficiency and effectiveness of operations within the company.
Collaborations
Prasiddha collaborates with talented colleagues, including Piyush Neupane and Anirudh Singh Shekhawat, to drive innovation and develop cutting-edge solutions in the field of machine learning.
Conclusion
Prasiddha Malla's contributions to machine learning and his innovative patent demonstrate his commitment to advancing technology in transaction processing. His work not only enhances operational efficiency but also sets a precedent for future innovations in the field.