Burlington, MA, United States of America

Kiran V Panchamgam

USPTO Granted Patents = 11 

Average Co-Inventor Count = 2.6

ph-index = 2

Forward Citations = 19(Granted Patents)


Location History:

  • Burlington, MA (US) (2019 - 2022)
  • Bedford, MA (US) (2019 - 2024)

Company Filing History:


Years Active: 2019-2025

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11 patents (USPTO):Explore Patents

Title: Kiran V Panchamgam: Innovator in Demand Modeling

Introduction

Kiran V Panchamgam is a notable inventor based in Burlington, MA, with a significant contribution to the field of demand modeling. He holds a total of 11 patents, showcasing his expertise and innovative approach to solving complex problems in this domain.

Latest Patents

Among his latest patents is the "Optimized Tree Ensemble Based Demand Model." This invention involves generating and training an optimized demand model for predicting the demand of an item. The process includes receiving a plurality of trees, each containing levels of splits and nodes corresponding to demand features that influence item demand. The model optimizes demand features using stored bounds to enhance prediction accuracy. Another patent under the same title focuses on training a tree ensemble machine learning model, which comprises multiple trees that correspond to demand features. This model generates an objective function for demand prediction and optimizes the model by determining optimal child nodes and feasible regions for each tree.

Career Highlights

Kiran has worked with prominent organizations, including Oracle International Corporation and the Massachusetts Institute of Technology. His experience in these institutions has contributed to his development as an inventor and innovator in the field of demand modeling.

Collaborations

Kiran has collaborated with notable individuals such as Su-Ming Wu and Aswin Kannan, further enhancing his work and contributions to the field.

Conclusion

Kiran V Panchamgam's innovative work in demand modeling and his impressive portfolio of patents highlight his significant impact on the industry. His contributions continue to shape the future of demand prediction and machine learning applications.

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