Emeryville, CA, United States of America

Gokul Narayanan Sathya Narayanan

This inventor holds 3 USPTO granted patents and 7 published patent applications and 3 EPO patents. Top assignee: Siemens Aktiengesellschaft. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Gokul Narayanan Sathya Narayanan. Retrieved from https://idiyas.com/inventor/gokul-narayanan-sathya-narayanan

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

USPTO Granted Patents = 3 

 

Average Co-Inventor Count = 5.5

ph-index = 1


Company Filing History:


Years Active: 2026

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3 patents (USPTO):Explore Patents

Title: Gokul Narayanan Sathya Narayanan: Innovator in Robotic Technologies

Introduction: Gokul Narayanan Sathya Narayanan is an inventive mind based in Emeryville, CA (US). He is currently associated with Siemens Aktiengesellschaft, where he contributes to advancements in robotic technologies. Although he has not yet been granted any patents, his work is focused on innovative solutions in the field.

Latest Patent Applications: Gokul has been involved in several notable patent applications. One of his latest applications is titled "Place Conditioned Pick for Robotic Pick and Place Operations." This method involves acquiring images of a pick scene and a placement area, computing object masks through instance segmentation, and selecting objects for robotic picking based on computed costs. Another significant application is "Realistic Depth Image Generation Using Generative Adversarial Nets." This system trains a generative adversarial network to produce realistic artificial depth images, which are essential for training deep learning networks used in robotic tasks.

Conclusion: Gokul Narayanan Sathya Narayanan is a promising inventor whose work in robotic technologies showcases his innovative spirit. His contributions, particularly in the realm of robotic picking and depth image generation, highlight the potential for future advancements in this field.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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