San Ramon, CA, United States of America

Hans Krupakar

USPTO Granted Patents = 2 

Average Co-Inventor Count = 6.0

ph-index = 1


Company Filing History:


Years Active: 2023-2025

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2 patents (USPTO):Explore Patents

Title: The Innovations of Hans Krupakar in Synthetic Training Data Generation

Introduction

Hans Krupakar, an inventive mind based in San Ramon, California, has made significant contributions to the field of machine learning through his innovative approach to synthetic training data generation. With one patent to his name, he focuses on enhancing model generalizability, an essential aspect in the realm of artificial intelligence.

Latest Patents

Krupakar’s patent, titled "Synthetic training data generation for improved machine learning model generalizability," introduces a range of systems and techniques designed to facilitate the generation of synthetic training data. This invention details a structured process involving three augmentation components: element augmentation, modality augmentation, and geometry augmentation. Each component effectively enhances the training datasets, allowing for improved results in machine learning models.

Career Highlights

Currently employed at GE Precision Healthcare LLC, Hans Krupakar is at the forefront of technology development within the healthcare sector. His work revolves around the integration of machine learning into healthcare solutions, demonstrating his commitment to advancing innovative practices in this critical field.

Collaborations

In his pursuit of innovation, Krupakar collaborates with experts such as Ravi Soni and Tao Tan. Together, they work on enhancing the effectiveness of machine learning models by leveraging diverse skill sets and insights, significantly contributing to the overall mission of GE Precision Healthcare.

Conclusion

Hans Krupakar represents a new wave of inventors dedicated to bridging the gap between technology and healthcare. Through his innovative patent in synthetic training data generation, he paves the way for more robust and generalizable machine learning applications. His contributions not only advance the field of artificial intelligence but also hold the potential for transformative impacts in healthcare technologies.

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