Princeton, NJ, United States of America

Michael Heilman

USPTO Granted Patents = 7 

Average Co-Inventor Count = 4.3

ph-index = 3

Forward Citations = 19(Granted Patents)


Company Filing History:


Years Active: 2015-2022

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7 patents (USPTO):Explore Patents

Title: Michael Heilman: Innovator in Automated Scoring Systems

Introduction

Michael Heilman is a prominent inventor based in Princeton, NJ (US), known for his contributions to the field of automated scoring systems. With a total of seven patents to his name, he has made significant strides in the application of deep learning technologies in educational assessments.

Latest Patents

One of Heilman's latest patents focuses on "Deep convolutional neural networks for automated scoring of constructed responses." This innovative system provides methods for automatically scoring constructed responses by processing them to generate a plurality of numerical vectors. A model is then applied to these vectors, which includes an input layer, intermediate layers, and an output layer designed to generate a score for the constructed response. This advancement has the potential to enhance the efficiency and accuracy of scoring in educational settings.

Career Highlights

Heilman is currently employed at Educational Testing Service, where he continues to develop and refine technologies that improve educational assessments. His work has been instrumental in integrating advanced computational techniques into traditional testing methodologies.

Collaborations

Heilman collaborates with notable colleagues such as Derrick Higgins and Nitin Madnani, contributing to a dynamic research environment that fosters innovation in educational technology.

Conclusion

Michael Heilman's work exemplifies the intersection of technology and education, showcasing how innovations in automated scoring can transform assessment practices. His contributions continue to influence the field and pave the way for future advancements.

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