Mumbai, India

Pradeep Moturi

This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Fractal Analytics Private Limited. Active years: 2026.

USPTO Granted Patents = 1 

% Patents Active = 100.0

Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Pradeep Moturi: Innovator in Graphic Layout Design

Introduction

Pradeep Moturi is a notable inventor based in Mumbai, India. He has made significant contributions to the field of graphic layout design through his innovative patent. His work focuses on enhancing the capabilities of large multimodal models, particularly in the realm of zero-shot graphic layout design generation.

Latest Patents

Pradeep Moturi holds a patent for "Visual prompting methods for GPT-4V based zero-shot graphic layout design generation." This patent explores how GPT-4-Vision (GPT-4V) large multimodal models can be utilized for versatile graphic layout design generation. The invention employs segmentation and superpixel methods to identify and mark key regions, visually augmenting images to enhance GPT-4V's spatial reasoning capabilities. The results indicate that these visual prompting methods outperform standard GPT-4V prompting techniques and perform comparably or even better than the LayoutDetr model in certain scenarios.

Career Highlights

Pradeep Moturi is currently associated with Fractal Analytics Private Limited, where he applies his expertise in innovative design methodologies. His work at Fractal Analytics has allowed him to collaborate with talented professionals in the field, further enhancing his contributions to graphic design technology.

Collaborations

One of his notable coworkers is Shivam, with whom he collaborates on various projects related to graphic layout design and multimodal models.

Conclusion

Pradeep Moturi's innovative approach to graphic layout design through his patent demonstrates his commitment to advancing technology in this field. His contributions are paving the way for more effective design methodologies and enhancing the capabilities of multimodal models.

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