Bengaluru, India

Mahendra Bisht


Average Co-Inventor Count = 10.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Mahendra Bisht: Innovator in Machine Learning Systems

Introduction

Mahendra Bisht is a prominent inventor based in Bengaluru, India. He has made significant contributions to the field of machine learning, particularly in the area of automated database element processing and prediction output generation. His innovative work has the potential to impact various sectors, especially in health management.

Latest Patents

Mahendra holds a patent for a groundbreaking invention titled "Machine learning systems for automated database element processing and prediction output generation." This computerized method involves training two machine learning models with historical feature vector inputs to generate likelihood and mean count outputs. The method processes likelihood feature vector inputs to predict the likelihood of avoidable negative health events for entities within a specified time period. Additionally, it processes mean count feature vector inputs to estimate the expected number of such events. The system automatically distributes structured campaign data to entities based on these outputs, showcasing a significant advancement in predictive analytics.

Career Highlights

Mahendra is currently associated with Cigna Intellectual Property, Inc., where he continues to develop innovative solutions in machine learning. His expertise in this domain has positioned him as a valuable asset to his organization and the broader tech community.

Collaborations

Throughout his career, Mahendra has collaborated with notable professionals, including David Fogarty and Yee Wah Eva Lee. These partnerships have fostered a collaborative environment that encourages innovation and the sharing of ideas.

Conclusion

Mahendra Bisht's contributions to machine learning and predictive analytics exemplify the impact of innovation in technology. His work not only advances the field but also holds promise for improving health outcomes through data-driven solutions.

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