Los Angeles, CA, United States of America

Benjamin D Goodman

USPTO Granted Patents = 2 

Average Co-Inventor Count = 14.0

ph-index = 1


Company Filing History:


Years Active: 2025

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2 patents (USPTO):Explore Patents

Title: The Innovations of Benjamin D. Goodman in Value Chain Network Planning

Introduction: Benjamin D. Goodman is an accomplished inventor based in Los Angeles, CA, known for his innovative contributions to the field of machine learning and digital twin simulation. With a focus on enhancing value chain networks, Goodman has secured a patent that exemplifies his expertise and foresight in integrating advanced technologies.

Latest Patents: Benjamin D. Goodman holds a patent for "Value Chain Network Planning Using Machine Learning and Digital Twin Simulation." This groundbreaking process involves receiving information through a digital twin representing the value chain network. The method utilizes a set of Artificial Intelligence (AI)-based learning models that are trained to classify various aspects such as operating states, fault conditions, and operational flows. Moreover, these models can determine tasks to be executed within the network, providing instructions or recommendations for executing those tasks effectively.

Career Highlights: Goodman is associated with Strong Force VCN Portfolio 2019, LLC, where he leverages his knowledge and skills to develop innovative solutions. His work emphasizes the integration of AI and simulation technologies, positioning him as a thought leader in the application of these advancements in value chain management.

Collaborations: Benjamin Goodman collaborates closely with Andrew Cardno, whose contributions supplement Goodman's innovative endeavors. Together, they foster an environment of creativity and technological advancement, driving forward the development of effective value chain strategies.

Conclusion: Benjamin D. Goodman stands out as a significant figure in the realm of innovations pertaining to value chains and artificial intelligence. His patent showcases the potential for machine learning in enhancing operational efficiencies within networks. As technologies continue to evolve, Goodman's work will undoubtedly inspire further advancements in the engineering and optimization of value chain networks.

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